Chapter 1 THE PROBLEM AND ITS BACKGROUND Chapter 1 of a thesis should contain a discussion of each of the following topics:

Introduction

Background of the study

Theoretical Framework

Conceptual Framework

Statement of the Problem

Assumptions and Hypotheses

Scope and Limitations of the Study

Significance or Importance of the Study

Definitions of Terms

The Introduction

Guidelines in writing the introduction. The introduction of a thesis should contain a

discussion of any or all of the following:

1. Presentation of the Problem. The start of the introduction is the

presentation of the problem, that is, what the problem is all about.

This will indicate what will be covered by the study. Example: Suppose

that the investigation is about the teaching of science in the high

schools of Province A. The discussion may start with this topic

sentence: There is no other period in world history when science has

been making its greatest impact upon humankind than it is today.

(Prolong the discussion citing the multifarious and wonderful benefits

that science is giving to humanity today. Later, in connection wit

science, the topic for inquiry may be presented as the teaching of

science in the high schools of Province A during the school year 1989-

1990 as perceived by the science teachers and students.)

2. The existence of an unsatisfactory condition, a felt problem that needs

a solution. Example: The teaching of science in the high schools of

Province A has been observed to be weak as shown by the results of

the survey tests given to the students recently. The causes must be

found so that remedial measures may be instituted. (The discussion

may be prolonged further)

3. Rationale of the study. The reason or reasons why it is necessary to

conduct the study must be discussed. Example: One of the Thrust of

the Department of Education, Culture and Sports and of the

government for that matter is to strengthen the teaching of science. It

is necessary to conduct this inquiry to find out how to strengthen the

instruction of science in the province. (This may be prolonged)

4. Historical background of the problem. For a historical background of

the research problem of the teaching of science, the first satellite to

orbited the earth, educational systems all over the world including that

the Philippines have been trying hard to improve their science

curricula and instruction, (This can be explained further)

5. A desire to have deeper and cleared understanding of a situation,

circumstance, or phenomenon. If the teaching of science in the high

schools of Province A is the topic, the researcher must explain his

earnest desire to have a deeper and clearer understanding of the

situation so that he will be in a better position to initiate remedial

measures.

6. A desire to find a better way of doing something or of improving a

product. The researcher must also explain his desire to find a better

way in teaching science in the high schools of Province A to improve

the outcome of instruction.

7. A desire to discover something. In connection with the teaching of

science in the high schools of Province A, the researcher may have the

desire to discover what is wrong with the instruction and a desire to

discover better ways of teaching the subject. He may discuss his

desire to discover such thing.

8. Geographical conditions of the study locale. This is necessary in

anthropological and economic studies. If the subject of investigation is

rice production, then the terrain, soil, climate, rainfall, etc. of the

study locale have to be described.

9. A link between the introduction and the statement of the problem. A

sentence or two should how the link between the introduction and the

conducting of the researcher. Example: The researcher got very much

interested in determining the status of teaching science in the high

schools of Province A and so he conducted this research.

Background of the study

This segment consists of statements on what led the investigator to launch the

study. A historical background may be given. Situations that may have spurred the

researcher to undertake the study are included. The background of the study may have

been generated by some empirical observations, the need to explore the problem and some

other relevant conditions.

Begin this section with a clear description of the background of the study and the

social, institutional context which will frame the project. Be careful to describe as clearly as

possible the problem intended to be addressed and refer to the relevant literature in the

field.

This section describes the history of the problem. That is, it is an overview of factors

which have led to the problem, comprise the problem and historical significance relative to

the problem. This should take between one (1) to one and a half (½) pages. (Salvador et

al.)

Theoretical Framework

This is the foundation of the research study. These are highly related theories and

principles that were established and proven by authorities which are very useful to the

present study. Almost all research studies that were conducted in the past were based on

universally accepted theories and principles.

Theoretical Framework means relating to or having the characteristic of the theory.

Theoretical Framework, therefore, refers to the set of interrelated construct, definitions, and

prepositions that presents a systematic view of phenomena by specifying relations among

variables. The theoretical framework becomes the basic of the research problem. It explains

the phenomena upon which the thesis investigation hopes to fill the vacuum in the stream

of knowledge.

Pursuing the linkage between the theory and the problem at hand, the researcher

views theoretical framework as an organized body that explains what has been done and

what has been said on the topic or problem being investigated. Moreover, the body of

knowledge establishes relationships among the variables concerned. The present study is

the missing link to the body of knowledge. Accordingly, if and when the research study is

consummated , the gap of missing link disappears since the study will have closed the gap.

The theoretical framework is now more complete until another researcher discovers another

gap, inconsistency, or weakness which will be the object of another investigation.

WHAT DATA MUST BE OBTAINED FROM A THEORY?

1. The name/s of author/s of the theory must be taken including the place and the time

/ year when he or she postulated such a principle or generalization.

2. Next, copy exactly the part or parts of the theory that are relevant to your study.

Make sure you will use a parenthetical reference to recognize the parts copied.

3. Finally, you will have to make a synthesis by relating to your findings what the

theory has to say about the phenomenon being studied. (Salvador et al.)

Conceptual Framework

From the review of related literature and studies, the researcher may formulate a

theoretical scheme for his research problem. This scheme is a tentative explanation or

theoretical explanation of the phenomenon or problem and serves as the basis for the

formulation research hypotheses. Thus, the conceptual framework consists of the

investigator’s own position on a problem after his exposure to various theories that have

bearing on the problem. It is the researcher’s new model which has its roots on the previous

models which the researcher had studied. (Sanchez, pp. 14-15)

The conceptual framework becomes the central theme, the focus, the main thrust of

the study. It serves as a guide in conducting investigation. Briefly stated, the conceptual

framework for the teaching of science can be: The effectiveness of a science instructional

program depends upon the qualifications of the teachers, the effectiveness of their methods

and strategies of teaching, the adequacy of facilities, the adequacy of supervisory

assistance, and the elimination of the problems hampering the progress.

Currently, however, most theses do not have a discussion of their conceptual

frameworks. Very few thesis writers endeavor to include an explanation of their conceptual

framework in their theses.

Paradigm. A paradigm is a diagrammatic representation of a conceptual

framework. It depicts in a more vivid way what the conceptual framework wants to convey.

Following are examples of a paradigm for the conceptual framework for the teaching of

science as mentioned above. A paradigm may take different diagrammatic forms.

Example 1

Inputs Process Outputs

Qualified

teachers Science Superior

science

Effective knowledge

methods

Instructional and

Adequate

facilities skills

Adequate Program of

Supervisory

assistance

Figure 8. Paradigm for science teaching in high school.

Statement of the Problem

There should be a general statement of the whole problem followed by the specific

questions or sub problems into which the general problem is broken up. These are already

formulated at the beginning of the study and so they should only be copied in this section.

(See the first section of the Statement of Problem, pp. 28-29, for further guidance in writing

the general problem and the specific questions pp. 29-30.)

Assumptions and Hypotheses

Historical and descriptive investigations do not need explicit hypotheses and

assumptions. Only experimental studies need expressly written assumptions and

hypotheses. Since these are already formulated at the start of the experiment, they are just

copied in this section. (See the sections Assumptions and Hypotheses, pp. 30-3, for further

guidance in writing assumptions and hypotheses).

Scope and limitations of the Study

Guidelines in writing the scope and delimitations. The scope and delimitations should

include the following:

1. A brief statement of the general purpose of the study.

2. The subject matter and topics studied and discussed.

3. The locale of the study, where the data were gathered or the entity to

which the data belong.

4. The population or universe from which the respondents were selected.

This must be large enough to make generalizations significant.

5. The period of the study. This is the time, either months or years,

during which the data were gathered.

Example: This investigation was conducted to determine the status of the teaching of

science in the high schools of Province A as perceived by the teachers and students

in science classes during the school year 1989-1990. the aspects looked into were

the qualifications of teachers, their methods and strategies, facilities forms of

supervisory assistance, problems and proposed solutions to problems.

General purpose: To determine the status of the teaching of science.

Subject matter: The teaching of science.

Topics (aspects) studied: Qualifications of teachers. Their methods and strategies,

facilities, form of supervisory assistance, problems and proposed solutions to the

problems.

Population or universe: teachers and students

Locale of the study: High schools of province A.

Period of the study: School year 1989-1990.

Limitations of the Study

Limitations of the study include the weaknesses of the study beyond the control of

the researcher. This is especially true in descriptive research where the variables involved

are uncountable or continuous variables such as adequacy, effectiveness, efficiency, extent,

etc. The weaknesses spring out of the inaccuracies of the perceptions of the respondents.

For instance, library facilities may be rated as very adequate by 50 students, fairly adequate

by 30 students, inadequate by 20 students, and very inadequate by 15 students. Certainly,

with these ratings, not all of them could be correct in their assessment. Some could have

inaccurate if not entirely wrong perceptions.

Importance or Significance of the Study

Guidance in explaining the importance of the study. The rationale, timeliness, and/or

relevance of the study to existing conditions must contain explanations or discussions of any

or all of the following:

1. The rationale, timeliness and/or relevance of the study. The rationale,

timeliness and/or relevance of the study to existing conditions must be

explained or discussed. For instance, a survey test in science reveals

that the performance of the students in the high schools of Province A

is poor. It must be pointed out that it is a strong reason why an

investigation of the teaching in science in the said high schools is

necessary. Also, the study is timely and relevant because today, it is

science and technology that are making some nations very highly

industrialized and progressive. So, if science is properly studied and

taught and then applied, it can also make the country highly

industrialized and progressive.

2. Possible solutions to existing problems or improvement to

unsatisfactory conditions. The poor performance of the students in the

high schools of Province A in a survey test in science should be

explained as a problem and an unsatisfactory condition. So if the

inquiry is made the possible causes of the poor performance of the

students in the science survey test may be discovered so that remedial

measures may be instituted to solve the problem or the unsatisfactory

situation.

3. Who are to be benefited and how they are going to be benefited. It

must be shown who are the individuals, groups, or communities who

may be placed in a more advantageous position on account of the

study. In the inquiry conducted about the teaching of science, for

instance, some weaknesses of the instructional program may be

discovered. This will benefit the administrators of the high schools in

Province A because they can make the findings of the study as a basis

of formulating their supervisory plans for the ensuing year. They may

include in their plans some measures to correct the weaknesses so as

to strengthen the instruction. In turn, the students will also benefit for

learning more science. In the long run, the whole country will enjoy

the good results of the study.

4. Possible contribution to the fund of knowledge. If in the study it is

found out that the inductive method is very effective in the teaching of

science, it should be pointed out that this can be a contribution of the

study to the fund of knowledge.

5. Possible implications. It should be discussed here that the implications

include the possible causes of the problems discovered, the possible

effects of the problems, and the remedial measures to solve the

problems. Implications also include the good points of a system which

ought to be continued or to be improved if possible.

Definition of Terms

Guidelines in defining terms:

1. Only terms, words, or phrases which have special or unique meanings

in the study are defined. For instance, the term non-teaching facilities

may be used in the study of the teaching of science. Non-teaching

facilities may be defined as facilities needed by the students and

teachers but are not used to explain the lesson or to make instructions

clearer. Examples are toilets or comfort rooms, electric fans, rest

rooms or lounges, and the like. They may also be called non-

instructional facilities.

2. Terms should be defined operationally, that is how they are used in

the study. For instance, a study is made about early marriage. What is

meant by early marriage? To make the meaning clear, early marriage

may be defined as one in which the contracting parties are both below

eighteen years of age.

3. The researcher may develop his own definition from the characteristics

of the term defined. Thus, a house of light materials may be defined as

one with bamboo or small wooden posts, nipa, buri, or nipa walls; split

bamboo floor and cogon or nipa roof. This is also an operational

definition.

4. Definitions may be taken from encyclopedias, books, magazines and

newspaper articles, dictionaries, and other publications but the

researcher must acknowledge his sources. Definitions taken from

published materials are called conceptual or theoretical definitions.

5. Definitions should a\be brief, clear, and unequivocal as possible.

6. Acronyms should always be spelled out fully especially if it is not

commonly known or if it is used for the first time.

Chapter 2 REVIEW OF RELATED LITERATURE AND STUDIES

Guidelines in Citing Related Literature and Studies

A. Characteristics of the Materials Cited

The following are the characteristics of related literature and studies that should be

cited: (Repeated for emphasis)

1. The materials must be as recent as possible. This is important because

of the rapid social, political, scientific, and technological changes.

Discoveries in historical and archeological research have also changed

some historical facts. Researchers in education and psychology are

also making great strides. So, finding fifteen years ago may have little

value today unless the study is a comparative inquiry about the past

and the present. Mathematical and statistical procedures, however, are

a little more stable.

2. Materials must be as objective and unbiased as possible. Some

materials are extremely one sided, either politically or religiously

biased. These should be avoided.

3. Materials must be relevant to the study. Only materials that have

some military to or bearing on the problem researched on should be

cited.

4. Materials must not too few but not too many. They must be sufficient enough

to give the researcher insight into his problem or to indicate the nature of the present

investigation. The number may also depend upon the availability of related materials. This is

especially a problem with pioneering studies. Naturally, there are few related materials or

even none at all. Ordinarily, from fifteen to twenty-five may do for a master’s thesis and

from twenty and above for a doctoral dissertation, depending upon their availability and

depth and length of discussions. The numbers, however, are only suggestive but not

imperative. These are only the usual numbers observed in theses and dissertations

surveyed. For an undergraduate thesis about ten may do.

B. Ways of Citing Related Literature and Studies

The following are the ways of citing related literature and studies:

1. By author or writer. In this method the ideas, facts, or principles,

although they have the same meaning, are explained or discussed

separately and cited in the footnote with their respective authors or

writers.

Examples: According to Enriquez, praise helps much in

learning, etc., (Enriquez, 1981)

Maglaque found out that praise is an important factor in

learning, etc., (Maglaque, 1984)

2. By topic. In this case, if different authors or writers have the same

opinion about the same topic, the topic is discussed and cited under

the names of the authors or writers. This is a summary of their

opinions. This is to avoid separate and long discussions of the same

topic.

Example: It has been found out that praise is an important aid

in learning of children. (Enriquez, 1981)

3. Chronological. Related materials may also be cited chronologically, that is,

according to the year they were written. Materials which were written earlier should be cited

first before those which were written later. This can be done especially when citation is by

author or writer. If citation is by topic, chronological citation can be done in the footnote.

C. What to Cite

It should be emphasized that only the major findings, ideas, generalizations,

principles, or conclusions in related materials relevant to the problem under investigation

should be discussed in this chapter. Generally, such findings, ideas, generalizations,

principles, or conclusions are summarized, paraphrased, or synthesized.

D. Quoting a Material

A material may be quoted if the idea conveyed is so perfectly stated or it is

controversial and it is not too long. It is written single spaced with wider margins at the left

and right sides of the paper but without any quotation marks.

Example: Suppose the following is a quotation: Said Enriquez,

Praise is an important factor in children’s learning. It

encourages them to study their lessons harder. Praise, however,

should be given appropriately.

Justification of the Study

It should be made clear that there is no duplication of other studies. The present

inquiry may only be a replication of another study. It should be stressed also that in spite of

similar studies, the present study is still necessary to find out if the findings of studies in

other places are also true in the locale of the present study. There may also be a need to

continue with the present investigation to affirm or negate the findings of other inquiries

about the same research problem or topic so that generalization or principles may be

formulated. These generalizations and principles would be the contributions of the present

investigation together with other studies to the fund of knowledge. This is one of the more

important purposes of research: the contribution that it can give to the fund of knowledge.

Synthesis

It should be emphasized in this area that the major findings, ideas, generalizations,

principles or conclusions in related materials relevant to the problem under investigation.

Generally, such findings, ideas, generalizations, principles or conclusions are summarized,

paraphrased, or synthesized.

Chapter 3 RESEARCH METHODOLOGY

Generally, the research design is explained in this chapter. Among those topics

included in the research design which need to be given some kind of explanations are the

following:

Methods of Research

Population, Sample Size, and Sampling Technique

Description of Respondents

Research instrument

Data-Gathering Procedure

Statistical Treatment of Data

Methods of Research

The method of research used whether historical, descriptive or experimental should

be explained briefly. The procedural part of the method, its appropriateness to the study,

and some of its advantages should be given attention and should be well discussed.

Example: Suppose the descriptive method of research was used in the study of the

teaching of science in the high schools of Province A. Briefly the discussion follows:

The descriptive method of research was used in this study. Descriptive method of

research is a fact-finding study with adequate and accurate interpretation of the findings. It

describes what is. It describes with emphasis what actually exist such as current conditions,

practices, situations, or any phenomena. Since the present study or investigation was

concerned with the present status of the teaching of science in the high schools of Province

A, the descriptive method of research was the most appropriate method to use. (This can be

elaborated further)

Population, Sample size and Sampling Technique

The researcher describes how he selected places, products, situations, and

respondents. If regions were used, the different regions of the country are included in his

first list. The next question is: how did the researcher select the sample regions included in

the study? Are the selected regions representative of all the regions that make up the

Philippines? If barrios in a particular province were the focus of the study, how did the

researcher select the few barrios representative of all the barrios? On the other hand, if

ethnic groups were used, how did he arrive at the majority and minority ethnic groups of

the particular national survey? The researcher should describe how he went about selecting

the sampled places and sampled products and respondents in this part of the methodology.

The Sampling Design

Before the collection of data starts in any research project, the proportion of the

population to be used must have been determined already and the computation of the

sample must have been finished. So, what the researcher has to do here is to write about

the complete procedure he used in determining his sample. Among the things that he

should explain are:

a. The size of the population;

b. The study population;

c. The margin of error and the proportion of the study population used;

d. The type or technique of sampling used whether pure random

sampling, cluster sampling or a combination of two or more

techniques;

e. The actual computation of the sample; and

f. The sample

The researcher must explain very clearly how he selected his sample. He must be

able to show that his sample is representative of the population by showing that he used

the appropriate technique of sampling. This is very important because if it appears that his

sample is not representative, his findings and conclusions will be faulty and hence, not valid

and reliable.

To be able to discuss and explain very well his sampling procedures, the researcher

must review sampling procedures in Chapter 12. Everything about sampling has been

discussed in that part of the book.

Description of Respondents

The respondents are described as a small group or as a big group. Characteristics

may include sex, age level, socio-economic status, marital status, level of intelligence,

education, type of community (urban or rural, barrio or town), ethnic group, and other

characteristics sought by the researcher to describe his respondents. These characteristics

of respondents could be presented in table form.

Research Instrument

Instrument used for gathering data are described under Research Methodology. The

various aspects of the instruments are mentioned. Items in each instrument are described

too. If validation of the test was made, this is also mentioned. In some studies, several

instruments are used. These could be related following the order of administration. It is

desirables that writers mention how these instruments were used in the study. Could it be

that Instrument 1 is intended to shed light on Hypothesis 1; Instrument 2 on Hypothesis 2;

and so forth?

If the instrument is lengthy, this is generally placed in the appendix. Such placement

has to be mentioned in the text and labeled as Appendix A,B, or C, as the case maybe.

This part describes the tools used to measure the variables. In most cases, this

means detailing the survey used. If a researcher developed a survey on his own or modified

one which is in the literature, he needs to include this plus the cover letter in the appendix.

If he is using a well- researched questionnaire, reference it clearly. (Salvador et al.)

Data-Gathering Procedure

The method of collecting data and the development of the instrument for gathering

data must also be explained.

Example: the method of collecting data used was the normative survey. This is

concerned with looking into the commonality of some elements. Since the present research

is a status study, the normative survey was the most appropriate method to use in

gathering data.

The instrument used to collect data was the questionnaire. This was used because it

gathers data faster than any other method. Besides, the respondents were teachers and

students and so they are very literate. They could read and answer the questionnaire with

ease.

Development of the instrument. After reading and studying samples of questionnaire

from related studies, the researcher prepared his own questionnaire. He also consulted

some knowledgeable people about how to prepare one. The researcher saw to it that there

were enough items to collect data to cover all aspects of the problem and to answer all the

specific questions under the statement of the problem. Then he submitted the questionnaire

to his adviser for correction after which it was finalized.

For validation purposes, the questionnaire was given to ten high school science

teachers for them to fill up. These teachers did not participate in the study. After they have

filled up the copies they were interviewed by the researcher to find out their assessment of

the questionnaire. They were asked if all the items were clear and unequivocal to them; if

the number of items were adequate enough to collect data about all aspects of teaching of

science; if the questions were interesting and not boring; if all the items were objective and

not biased except for a few unavoidable essay questions; if all the items were relevant to

the research problem; and if the questionnaire were not too long. All of them said the items

were clear and unequivocal except a few, relevant, interesting and objective questions, and

the length was alright. The few questioned items were revised for more clarity and

definiteness.

The copies of the questionnaire were then distributed personally by the researcher to

the respondents. After a few days, all the copies distributed were retrieved also personally

by the researcher. (The discussion may be extended)

WAYS OF COLLECTING DATA

1. Mechanical devices include almost all tools (such as microscopes, telescopes,

thermometers, rulers and monitors) used in physical sciences.

2. Clerical tools are used when the researcher studies people and gather data on the

feeling, emotions, attitudes and judgment of the subject.

2.1 Questionnaire method

2.2 Interview method

2.3 Empirical observation method

2.4 Registration method

2.5 Testing method

2.6 Experiment method

2.7 Library method

Questionnaire Method. This is a list of planned, written questions, related to a

particular topic with space provided for indicating response to each question intended

for submission to a number of people for a reply. It is commonly used in normative

studies and in the measurements of attitudes and opinions.

Guidelines in the Formulation of Questions in a Questionnaire

1. Make all directions clear and unequivocal.

2. Use correct grammar.

3. Make all questions unequivocal.

4. Avoid asking biased questions.

5. Objectify the responses.

6. Relate all questions to the topic under study.

7. Create categories or classes for approximate answers.

8. Group the questions in local sequence.

9. Create sufficient number of response categories.

10. Word carefully or avoid questions that deal with confidential and embarrassing

information.

11. Explain and illustrate different questions.

12. State all questions affirmatively.

13. Place all space for replies at the left side.

Interview Method. This is a purposeful face-to-face relationship between person, one

called the interviewer who asks questions to gather information and to the other

called the interviewee or the respondent who supplies the information asked for.

This is feasible when a person interact is available. The research interview is a

research method that involves situations or conditions the respondent is in, although

it entails difficulty in tallying as the answers are varied. In other words, the answer is

entirely left at the discretion on the respondent.

In general, respondents do not like to answer open-ended questionnaires for aside

from giving multiple responses, they feel that they are taking an examination. Aside

from this, an open-ended questionnaire gives multiple responses, which makes

statistical analysis difficult. (Salvador et al.)

Statistical Treatment of Data

The last part of this chapter usually describes the statistical treatment of data. The

kind of statistical treatment depends upon the nature of the problem, especially the specific

problems and the nature of the data gathered. The explicit hypotheses particularly

determine the kind of statistics to be used.

The role of statistics in research. With the advent of the computer age, statistics is

now playing a vital role in research. This is true especially in science and technological

research. What functions do statistics perform in research? Some are the following:

1. Statistical methods help the researcher in making his research design,

particularly in experimental research. Statistical methods are always

involved in planning a research project because in some way statistics

directs the researcher how to gather his data.

2. Statistical techniques help the researcher in determining the validity

and reliability of his research instruments. Data gathered with

instruments that are not valid and reliable are almost useless and so

the researcher must have to be sure that his instruments are valid and

reliable. Statistics helps him in doing this.

3. Statistical manipulations organize raw data systematically to make the

latter appropriate for study. Unorganized data cannot be studied. No

inferences or deductions can be made from unorganized data.

Statistics organized systematically by ordered arrangement, ranking,

score distribution, class frequency distribution or cumulative

frequencies. These make the data appropriate for study.

4. Statistics are used to test the hypotheses. Statistics help the

researcher to determine whether these hypotheses are to be accepted

or to be rejected.

5. Statistical treatments give meaning and interpretation to data. For

Instance, if the standard deviation of the class frequency of a group is

small, we know that the group is more or less homogeneous but if it is

large, the group is more or less heterogeneous.

6. Statistical procedures are indispensable in determining the levels of

significance of vital statistical measures. These statistical measures are

the bases for making inferences, interpretations, conclusions or

generalizations.

Some guidelines in the selection and application of statistical procedures. The

researcher must have at least a rudimentary knowledge of statistics so that he will be able

to select and apply the appropriate statistical methods for his data. Some suggestions for

the selection and application of statistical techniques follows:

1. First of all, the data should be organized using any or all of the

following depending upon what is desired to be known or what is to be

computed: talligram (tabulation table), ordered arrangement of

scores, score distribution, class (grouped) frequency distribution, or

scattergram.

2. When certain proportions of the population based on certain variables

such as age, height, income, etc. are desired to be known, frequency

counts with their frequency percents may be used. For further

analysis, cumulative frequencies (up and down) with their respective

cumulative frequency percents (up and down) may also be utilized.

For example, a specific question is “How the high school science

teachers of province A may be described in terms of sex?” The males

were counted and the females were also counted and their respective

percent equivalents were computed.

3. When the typical, normal, or average is desired to be known, the

measures of central tendency such as the median, the mean or the

mode may be computed and used.

4. When the variables being studied are abstract or continuous such that

they cannot be counted individually such as adequacy, efficiency,

excellence, extent, seriousness (of problems), and the like, the

weighted mean may be computed and used if the average is desired to

known. The variable is divided into categories of descending degree of

quality and then each degree of quality is given a weight. For instance,

the question is “How adequate are the facilities of the school?”

Adequacy may be divided into five degrees of quality such as “very

adequate” with a weight of 5, “adequate” with a weight of 4, “Fairly

adequate” with a weight of 3, “inadequate” with a weight of 2, and

“very inadequate” with a weight of 1. Then the weighted mean is

computed.

5. When the variability of the population is desired to be known, the

measures of variability such as the range, quartile deviation, average

deviation or the standard deviation may be computed and used. When

the measure of the variability or dispersion is small, the group is more

or less homogenous but when the measure of variability is large, the

group is more or less heterogeneous.

6. When the relative placements of scores or positions are desired to be

known, ranking, quartile or percentile rank may be computed and

used. These measures indicate the relative positions o scores in an

ordered arrangement of the scores.

7. When the significance of the trend of reaction or opinion of persons as

a group toward a certain issue, situation, value or thing is desired to

be known but in which there is a neutral position, the chi-square of

equal probability, single group, is computed and interpreted.

8. When the significance of the difference between the reactions, or

opinions of two distinct groups in which there is a neutral position is

desired to be known, the chi-square of equal probability, two-group, is

computed and used.

For instance, a group of 50 persons, 25 males and 25 females,

were asked to give their reactions may be “Strongly agree”, “Agree”,

“Undecided or No opinion”, “Disagree”, or “Strongly disagree”. If the

persons are considered as a group, the chi-square of equal probability,

single group is computed as in No. 7. However, if the significance of

the difference between the reactions of the males and those of the

females is to be studied, the chi-square of equal probability, two-

group, is applied as in No. 8.

9. To determine how one variable varies with one another, the coefficient

of correlation is computed, as for instance, how the scores of a group

of students in English test. This is also used to determine the validity

of a test by correlating it with a test of known validity. When the

coefficient of correlation between two tests is known and a prediction

is to be made as to what score a student gets in a second test after

knowing his score in the first, the so-called regression equation is to

be utilized.

10. If the significance of the difference between the perceptions of two-

groups about a certain situation is to be studied, the computation of

the difference between means is to be made. Example: Is there a

significant difference between the perceptions of the teachers and

those of the students about the facilities of the school? To answer this

question, the significance of the difference of two means is to used.

The statistical measure computed is called t.

The t is also used to determine the usefulness of a variable to

which one group called the experimental group is exposed and a

second group called control group is not exposed. For instance, the

question is: Does guidance improve instructions?” Create two matched

groups and expose one group to guidance while the control group is

not exposed to guidance. At the end of the experimental period, give

the same test to the two groups. Then compute the t which will show if

guidance is an effective aid to instruction.

11. To determine the relative effectiveness of the different ways of doing

things to which different randomized groups are respectively exposed

to and only a post test is given to the different groups, analysis of

variance is appropriate to use. For instance, a teacher wants to find

out the relative effectiveness of the following methods of

communication: pure lecture, lecture-demonstration, recitation-

discussion, and seminar type of instruction in science. Four groups of

students are formed randomly and each assigned to one method. The

four groups study the same lessons and after a certain period given

the same test. By analysis of variance, the relative effectiveness of the

four methods will be revealed.

If the four groups are given pre-test and a post-test, the

analysis of covariance is utilized.

12. To determine the effects of some variables upon a single variable to

which they are related, partial and multiple correlations are suggested

to be used. For example, the question is: Which is most related to the

passing of a licensing engineering examination: college achievement

grades, or percentile ranks in aptitude tests, general mental ability

test, vocational and professional interest inventory, or National College

Entrance Examination? The process of partial and multiple correlations

will reveal the pure and sole effect of each of the independent

variables upon the dependent variable, the passing of the licensing

examination.

13. To determine the association between two independent variables, the

chi-square of independence or chi-square of multiplication may be

used. The question answered by this statistical process is: Is there an

association between education and leadership? Or, the level of

education and the ability to acquire wealth? Or, between sociability

and economic status?

Indeed, there are lots of research situations in which different

statistical procedures may or can be used and if the researcher is not

so sure that he is in the right path, he better consult good statistical

books, or acquire the services of a good statistician plus the services

of a computer especially if the statistical procedures are complex ones.

Chapter 4 ANALYSES, PRESENTATION, AND

INTERPRETATION OF DATA

In this chapter, the researcher makes his analysis, presentation, and interpretation

of his data.

Analysis

Analysis is the process of breaking up the whole study into its constituent parts of

categories according to the specific questions under the statement of the problem. This is to

bring out into focus the essential features of the study. Analysis usually precedes

presentation.

Example: In the study of the teaching of science in the high schools of Province A,

the whole study may be divided into its constituent parts as follows according to the specific

questions:

1. Educational qualifications of the science teachers

2. Methods and strategies used in the teaching of science

3. Facilities available for the teaching of science

4. Forms of supervisory assistance

5. Differences between the perception of the teachers and those of the

students concerning the teaching of science

6. Problems encountered in the teaching of science

7. Proposed solutions to the problems

8. Implications of the findings

Each constituent part may still be divided into its essential categories. Example: The

educational qualifications of the teachers may further be subdivided into the following:

1. Degrees earned in pre-service education

2. Majors or specializations

3. Units earned in science

4. Teacher’s examinations and other examinations passed

5. Seminars, conferences, and other special trainings attended for the

teaching of science

6. Books, journals, and other materials in science being read

7. Advanced studies

8. Number of years in science teaching

9. Etc.

Then under degrees earned are

1. Bachelor of Arts

2. Bachelor of Science in Education

3. Master of Arts

4. Etc.

The other constituent parts may also be similarly divided and subdivided. The data

are then grouped under the categories or parts to which they belong.

Classification of data. Classification is grouping together data with similar

characteristics. Classification is a part of analysis. The bases of classification are the

following:

a. Qualitative (kind). Those having the same quality or are of the same

kind are grouped together. The grouping element in the examples

given under analysis is qualitative. See examples under analysis.

b. Quantitative. Data are grouped according to their quantity. In age, for

instance, people may be grouped into ages of 10-14, 15-19, 20-24,

25-29, etc.

c. Geographical. Data may be classified according to their location for

instance; the schools in the secondary level in Province A may be

grouped by district, as District 1, District 2, District 3, etc.

d. Chronological. In this, data are classified according to the order of

their occurrence. Example: The enrolments of the high schools of

Province A may be classified according to school years, as for,

instance, enrolments during the school years 1985-’86, 1986-’87,

1987-’88.

Cross-classification. This is further classifying a group of data into subclasses. This is

breaking up or dividing a big class into smaller classes. For instance, a group of students

may be classified as high school students as distinguished from elementary and college

students. Then they are further subdivided into curricular years as first, second, third, and

fourth years. Each curricular year may still be subdivided into male and female.

Arrangement of data or classes of data. The bases of arrangement of data or groups

of data are the same as those of classification.

a. Qualitative. Data may be arranged alphabetically, or from the biggest

class to the smallest class as from the phylum to specie in classifying

animals or vice versa, or listing the biggest country to the smallest one

or vice versa, or from the most important to the least important, or

vice versa, etc. Ranking of students according to brightness is

qualitative arrangement.

b. Quantitative. This is arranging data according to their numerical

magnitudes, from the greatest to the smallest number or vice versa.

Schools may be arranged according to their population, from the most

populated to the least populated, and so with countries, provinces,

cities, towns, etc.

c. Geographical. Data may be arranged according to their geographical

location or according to direction. Data from the Ilocos region may be

listed from north to south by province as Ilocos Norte, Abra, Ilocos Sur

and La Union.

d. Chronological. This is listing down data that occurred first and last

those that occurred last or vice versa according to the purpose of

presentation. This is especially true in historical research. For instance,

data during the Spanish period should be treated first before the data

during the American Period.

Classification, cross-classification and arrangement of data are done for purposes of

organizing the thesis report and in presenting them in tabular form. In tables, data are

properly and logically classified, cross-classified, and arranged so that their relationships are

readily seen.

Group-derived Generalizations

One of the main purposes of analyzing research data is to form inferences,

interpretations, conclusions, and/or generalizations from the collected data. In so doing the

researcher should be guided by the following discussions about group-derived

generalizations.

The use of the survey, usually called the normative survey, as a method of collecting

data for research implies the study of groups. From the findings are formulated conclusions

in the form of generalizations that pertain to the particular group studied. These conclusions

are called group-derived generalizations designed to represent characteristics of groups and

are to be applied to groups rather than to individual cases one at a time. These are

applicable to all kinds of research, be they social, science or natural science research. There

are several types of these but are discussed under four categories by Good and Scates.

(Good and Scates, pp. 290-298) The key sentences are of this author.

1. Generally, only proportional predictions can be made. One type of

generalization is that which is expressed in terms of proportion of the cases in a group,

often in the form of probability. When this type is used, we do not have enough information

about individual cases to make predictions for them, but we can nevertheless predict for a

group of future observations. As to individual event, however, we can say nothing;

probability is distinctly a group concept and applies only to groups.

Quality control in manufacturing is an example. Based on the recognition that

products cannot be turned out as precisely as intended, but that so long as a given

proportion of the cases fall within assigned limits of variation, that is all that is expected. In

the biological field, certain proportions of offspring, inherit certain degrees of characteristics

of parents, but individual predictions cannot be made. In the social field, in insurance

especially, based on demographic and actuarial data, life tables indicate life expectancies of

groups but nothing whatsoever is known about the life expectancy of any particular

individual.

Here is another example. Suppose in a certain school offering civil engineering, it is a

known fact that all through the years, bout 70% of its graduates with an average of 2.0 or

its equivalent or higher pass the licensing examination for civil engineers. On this basis, we

can predict that about 70% of the graduates of the school with an average of 2.0 or higher

will pass the next licensing examination for civil engineers but we cannot predict with

certainty the passing of a particular graduate even if his average grade is 1.25.

2. The average can be made to represent the whole group. A second type of

group-derived generalization results from using the average as a representation of the

group of cases and offering it as a typical result. This is ignoring the individuals comprising

the group or the variation existing in the group but the average represents the whole group.

Generally, the mean and the median are used to denote the averages of scale position but

other statistical measures such as the common measures of variation, correlation,

regression lines, etc. are also structurally considered as averages. These are group

functions conveying no sure knowledge about any individual case in the group.

3. Full frequency distribution reveals characteristics of a group. As a third type

of knowledge growing out of the study of the groups, we have the full-frequency distribution

– the most characteristics device, perhaps of all statistical work. Perhaps, too the most

inferential characteristics of frequency distribution are shape and spread. Frequency

distributions carry the implication of probability. One implication is as follows. Suppose the

heights of a Grade I pupils are taken and then grouped into a class frequency distribution,

using height as the trait or basis of distributions in groups. Then the suppliers of chairs and

tables for the pupils will be able to know the number of chairs and tables to suit the heights

of the pupils.

Here is another example which enables us to know certain characteristics of a group.

Suppose a test is given to a group of students. Then their scores are grouped into a class

frequency distribution. If the standard deviation, a measure of variability, is computed and

it is unusually large, then we know that the group is heterogeneous. If the standard

deviation is small, the group is more or less homogeneous. If the distribution is graphed and

the curve is bell-shaped, the distribution is normal, that is, there is an equal number of

bright and dull students with the average in the middle. If the curve is skewed to the right,

there are more dull students than bright ones, and if the distribution is skewed to th left

there are more bright students than dull ones.

4. A group itself generates new qualities, characteristics, properties, or aspects

not present in individual cases. For instance, there are many chairs in a room. The chairs

can be arranged in a variety of ways. However, if there is only one chair, there can be no

arrangement in any order. Hence, order and arrangement are group properties and they

represent relationships within a group, properties which can arise only if there are two or

more cases.

Other group properties that exist only in groups are cooperation, opposition,

organization, specialization, leadership, teaching, morale, reciprocal sharing of emotions,

etc. which vanish in individual cases.

Two or more categories of generalization may be added at this point.

1. A generalization can also be made about an individual case. For instance, a

high school graduating student is declared valedictorian of his class. We can generalize that,

that student is the brightest in his class. This is a group-derived generalization because it

cannot be made if there is only one student. Here is another example. A teacher declares

that Juan is the best behaved pupil in her class. This is a group-derived generalization

because this statement cannot be made if there is only one pupil. There are many instances

of this kind.

2. In certain cases, predictions on individual cases can be made. It has been

mentioned earlier that, generally, only proportional predictions can be made. However, in

correlation and regression studies, one variable can be predicted from another. Take the

case of the civil engineering graduate taking the licensing examination by the use of

regression equations. The accuracy of prediction is high if (1) there is linearity in the

relationship of the two variables if graphed, (2) the distributions in the two variables are

normal or not badly skewed, and (3) the spread or scatter of the two variables is the same

for each column or row in the correlation table. The process involves a complicated

statistical book especially that of Garrett, pp. 122-146 for linear correlation and pp. 151-165

for regression and prediction.

Preparing Data for Presentation

Before presenting data in accepted forms, especially in presenting them in the form

of statistical tables, they have to be tallied first in a tabulation diagram which may be called

talligram, a contraction of tally and diagram. The individual responses to a questionnaire or

interview schedule have to be tallied one by one.

How to construct a talligram. A talligram may be constructed as follows:

1. Determine the classes and their respective subclasses along with their

respective numbers. For instance, in the study about science teaching

in the high schools of Province A, anent the qualifications of the

teachers, suppose there are four degrees earned by the teachers such

as AB (Bachelor of Arts), BSCE (Bachelor of Science in Civil

Engineering), BSE (Bachelor of Science in Education) and MA (Master

of Arts with undergraduate courses). The subclasses are the

specializations or majors of the teachers. There are also four such as

English, History, Mathematics, and Science. The classes and their

subclasses are arranged alphabetically.

2. Make rows for the classes by drawing horizontal lines with appropriate

spaces between the lines and the number of the rows should be two

more than the number of classes. So in the example given in step no.

1, there should be six rows because there are four classes. The

uppermost row is for the labels of the subclasses, the bottom row is

for the totals, and the middle four rows are for the classes: AB, BSCE,

BSE, and MA.

3. Make columns for the subclasses by drawing vertical lines with

appropriate spaces between the lines and the number of columns

should be two more than the number of subclasses. So in the example

in No. 1 step there should six columns. The leftmost column is for the

labels of the class rows, the rightmost column is for totals, and the

four middle columns are for the four subclasses.

See Figure 1 for an example of talligram.

Degrees and Specializations of Teachers

Degrees Specializations (Majors) Total

English History Mathematics Science

AB 1 11 1111 1 1111 1111 11 21

BSCE 1111 4

BSE 11 11 1111 1111 1111 1111 1111 111 31

MA 1 11 3

Totals 3 4 25 27 59

Figure 1

How to tally data (responses) gathered through a questionnaire. Tallying responses

to a questionnaire in a talligram follows. Suppose a questionnaire gives the following data:

a. Teacher A is an AB graduate with a science major. Enter a tally in the

cell which is the intersection of the AB row and the Science column.

The tally is a short vertical bar. See Entry (1) in Figure 1.

b. Teacher B is an AB graduate with a science major. Enter a tally in the

cell which is the intersection of the AB row and the Science column.

See Entry (2) in Figure 1.

c. Teacher C is a BSE graduate with a science major. Enter a tally in the

cell which is the intersection of the BSE row and the Science column.

See Entry (3) in Figure 1.

d. Teacher D is a BSE graduate with mathematics major. Enter a tally in

the cell which is the intersection of the BSCE row and the Mathematics

column. See Entry (4) in Figure 1.

e. Teacher E is a BSCE graduate with mathematics major. Enter a tally in

the cell which is the intersection of the BSCE row and the Mathematics

column. See Entry (5) in Figure 1.

f. Continue the process until all the data needed are entered.

When finished, the talligram will look exactly like Figure 2.

Degrees and Specializations of the Teachers

Degrees

Specializations (Majors)

Totals

English

History

Mathematics

Science

AB 1 11 1111 1 1111 1111 11 21

BSCE 1111 4

BSE 11 11 1111 1111 1111 1111 1111 111 31

MA 1 11 3

Totals 3 4 25 27 59

Figure 2

Figure 2 may now e\be converted into a statistical table for data presentation.

Generally, all quantified data are tallied first in talligram which are then converted into

statistical tables for data presentation using Hindu-Arabic numerals in the cells in place of

tallies.

Presentation of Data

Presentation is the process of organizing data into logical, sequential, and meaningful

categories and classifications to make them amenable to study and interpretation. Analysis

and presentation put data into proper order and in categories reducing them into forms that

are intelligible and interpretable so that the relationships between the research specific

questions and their intended answers can be established. There are three ways of

presenting data; textual, tabular, and graphical.

Textual Presentation of Data

Textual presentation uses statements with numerals or numbers to describe data.

The main aims of textual presentation are to focus attention to some important data and to

supplement tabular presentation.

The disadvantage, especially if its too long, is that it is boring to read and the reader

may not even be able to grasp the quantitative relationships of the data presented. The

reader may even skip some statements.

Example: The following refers to the degrees earned by 59 science teachers in the

hypothetical study of the teaching of science in the high schools of Province A:

Of the 59 science teachers, 21 or 35.59 percent have earned a bachelor of Arts

degree with education units, four or 6.78 percent have earned a Bachelor of Science in Civil

Engineering degrees with education units, 31 or 52.54 percent a Bachelor of Science in

Education degree, and three or 5.08 percent a Master of Arts degree.

According to government regulations, all the teachers are qualified to teach in the

high school. (This is already a finding, interpretation, or inference)

Tabular Presentation of Data

Statistical table defined. A statistical table or simply table is defined as a systematic

arrangement of related data in which classes of numerical facts or data are given each a

row and their subclasses are given ach column in order to present the relationships of the

sets or numerical facts or data in a definite, compact, and understandable form or forms.

Advantages of tabular over textual presentation of data. The advantages of the

tabular over the textual presentation of data are:

1. Statistical tables are concise, and because data are systematically

grouped and arranged, explanatory matter is minimal.

2. Data are more easily read, understood and compared because of their

systematic and logical arrangement into rows and columns. The reader

can understand and interpret a great bulk of data rapidly because he

can see significant relationships of data at once.

3. Tables give the whole information even without combining numerals

with textual matter. This is so because tables are so constructed that

the ideas they convey can be understood even without reading their

textual presentation.

The major functional parts of a statistical table. The names of the functional parts of

a statistical table are shown in the following diagrams: (Bacani, et. Al, p. 55)

Table Number

Title

(Head note)

Stub Head

Master Caption

Column

Caption

Column

Caption

Column

Caption

Column

Caption

Row Label Entry Entry Entry Entry

“ “ “ “ “ “

“ “ “ “ “ “

“ “ “ “ “ “

“ “ “ “ “ “

“ “ “ “ “ “

“ “ “ “ “ “

Total

The above illustration of a table is only a simple one. There are tables that are very

complicated. For instance, the column captions may further be subdivided into sub-column

captions which in turn may still be subdivided. This happens when the subject matter of the

table is classified, then the first classifications are further sub classified, and so on.

1. Table Number. Each table should have a number, preferably in Arabic, for

reference purposes. This is because only the table numbers are cited. The number is written

above the title of the table. Tables are numbered consecutively throughout the thesis

report. If there is only one table the number is unnecessary. See table 1 for illustration.

2. Title. The title should tell about the following:

a. The subject matter that said table deals with;

b. where such subject matter is situated, or from whom the data

about such subject matter were gathered;

c. when data about such subject matter were gathered or the

time period when such data were existent; and

d. sometimes how the data about such subject matter are

classified.

Usually, however, only the first two elements are mentioned in the title, and

occasionally only the subject matter. This is possible if the time period of the study as well

as the locale and respondents are well discussed in the scope and delimitation of the study.

Only the beginning letters of the important words in the title are capitalized. If the title

contains more than one line, it should be written like an inverted pyramid. See Table 1

below.

Table 1

Degrees and Specializations of the Teachers

Degrees

Earned a

Specializations (Majors) Totals

English History Mathematics Science

Fb % F % F % F % F %

AB 1 1.69 2 3.39 6 10.17 12 20.34 21 35.59

BSCE 4 6.78 4 6.78

BSE 2 3.39 2 3.39 14 23.73 13 22.03 31 52.54

MA 1 1.69 2 3.39 3 5.08

Totals 3 5.08 4 6.78 25 42.37 27 45.76 59 99.99c

3. Headnote or Prefatory Note. This is written below the title and it is usually

enclosed in parentheses. It explains some things in the table that are not clear. Suppose a

table entitled “Monetary Values or Properties of the High Schools in Province A” is to be

constructed and the entries in the table are in rounded millions of pesos. If the amount to

be entered is six million pesos, the entry is only 6, instead of entering 8,000,000 the entry

is only 8, etc. The Headnote that should be written below the title should be written below

the title should be “Millions of Pesos.” So, the entry of 6 is read six million pesos, the entry

of 8 should be read eight million pesos, etc.

4. Stub. The stub contains the stub head and the row labels. The stub head tells

what the stub contains, the row labels. Each row label describes the data contained in that

row. In the table given as example, Table 1, Degrees is the stub head and below it are the

degrees which are the row label: AB, BSCE, BSE, and MA. In the AB row all the teachers

listed there are AB graduates, in the BSCE row all BSCE graduates, in the BSE row, all BSE

graduates, and in the MA row, all MA graduates. Totals may be considered as part of the

stub.

5. Box Head. The box head contains the master caption, the column captions,

and the column sub captions. The master caption describes the column captions and the

column captions in turn describe the sub column captions. In Table 1, the master caption is

Specializations (Majors). The column captions are English, History, Mathematics, Science,

and Totals. The sub captions are F (frequency), and % (percent). The F indicates the

number of teachers under it and the symbol % indicates the proportion of the number under

F to the total, 59.

6. Main body, field or text. The main body, field or text of the table contains all

the quantitative and/or proportional information presented in the table in rows and in

columns. Each numerical datum is entered in the cell which is the intersection of the row

and the column of the datum. For instance, the 14 teachers who are BSE graduates and

who majored in mathematics are centered in the cell which is the intersection of the BSE

row and the mathematics column.

7. Footnote. The footnote which appears immediately below the bottom line of

the table explains, qualifies, or clarifies some items in the table which are not readily

understandable or are missing. Proper symbols are used o indicate the items that are

clarified or explained. In Table 1, a is used to indicate that all the teachers have enough

education units, b is used to indicate that all percents were computed with 59 as the base,

and c is used to indicate that the total percent does not equal 100.00 due to the rounding

off of the partial percents to two decimal places.

The footnote is not necessary everything in the table is clear and there is nothing to

clarify or explain.

8. Source note. The source note which is generally written below the footnote

indicates the origin or source of the data presented in the table. In Table 1, the sources of

the data are the Principals’ Offices. The purposes of placing the source note are:

a. To give credit or recognition to the author of the table or the

source or sources of the data;

b. To allow the user to secure additional data from the same

source;

c. To provide the user a basis for determining the accuracy and

reliability of the information provided by the table; and

d. To protect the maker of the table against any charge of

inaccuracy and unreliability.

The source note is not necessary if the sources of the data are the respondents to a

questionnaire or interview schedule.

Ruling and spacing in tables. Ruling is done in a table to emphasize or make clear

relationships. There are no fixed standard rules to follow in ruling and spacing tables.

Emphasis and clarity are the determining factors. However, the following guidelines are

generally followed in the construction of tables for a thesis report:

1. The table number is not separated by line from the title. It is written

two spaces above the title.

2. The title is separated from the rest of the table by a double line placed

two spaces below the lowest line of the title.

3. The stub, master caption, captions, sub-captions, and totals are

separated from one another by vertical and horizontal lines.

4. The rows and columns are not separated by lines. Major groups,

however, are separated by single lines. For purposes of clarity, rows

are separated by a double space and the columns are separated by as

wide a space as possible.

5. Both ends of the table are unruled.

6. There is always a line, either ingle or double, at the bottom of the

table.

Unity in a table. There should always be unity in a table. To achieve this, presenting

too many ideas in a single table should be avoided. One subject matter is enough, one that

can be divided into categories which in turn can be divided into common classifications. In

Table 1, for instance, the subject matter is degrees and majors. Degrees are divided into

similar categories such as AB, BSCE, BSE, and MA. The sub classes such as English, History,

Mathematics, and Science are common to the degree categories.

Textual presentation of tabular data. Generally, there should be a textual

presentation of table which precedes the table or the table may be placed within the textual

presentation. The table and its textual presentation should be placed as near as possible to

each other. Textual presentation is mixing words with numbers in statements.

There are two ways of making a textual presentation of a table:

1. All the items in the table are textually presented. This manner enables

the reader to comprehend the totality of the data even without

consulting the table. This is alright if the data are not so many.

However, if the data are so numerous, reading becomes boring and

the reader may even skip some of the items.

2. Only the highlights or important parts of the data are textually

presented.

The basic principles that should be remembered in the textually presentations of a

table are:

1. The textual presentation of a table should be as complete as possible

so that the ideas conveyed in the table are understood even without

referring to the table itself.

2. Textual Presentation is generally followed by interpretation, inference

or implication. This is done after the data from the table have been

textually presented.

3. Findings in the present study should be compared with the findings of

other studies as presented in the related literature and studies. This

enables the researcher to make some generalizations if there are

enough data to support such generalizations.

Following is the textual presentation of Table 1:

(Complete) Table 1 shows that there were 59 science teachers in the high schools of

Province A. of this number, 21 or 35.59 percent were AB graduates. Of the AB graduates,

one or 1.69 percent majored in English, two or 3.39 percent in History, six or 10.17 percent

in Mathematics, and 12 or 30.34 percent in Science.

There were only four or 6.78 percent who were BSCE graduates, all majoring in

Mathematics.

There were 31 or 52.54 percent who were BSE graduates and of this number, two or

3.39 percent majored in English, the same number in History, 14 or 23.73 percent in

Mathematics, and 13 or 22.03 percent in Science.

Summarizing the majors, three or 5.08 percent were majors in English, four or 6.78

percent in History, 25 or 42.37 percent in Mathematics, and 27 or 45.76 percent in Science.

Summarizing the majors, three or 5.08 percent were majors in English, four or 6.78

percent in History, 25 or 42.37 percent in mathematics, and 27 or 45.76 percent in Science.

(Only the highlights) Of the 59 teachers, the AB and BSE graduates constituted the

most number. Twenty-one or 35.39 percent were AB graduates and 31 or 52.54 percent

had BSE degrees or a total of 52 or 88.13 percent. Of the majors, 27 or 45.76 percent of

the teachers were majors in Science, 25 or 42.37 percent in Mathematics, and three or 5.08

percent in English and four or 6.78 percent in History.

Findings. Findings are the original data, quantitative or otherwise, derived taken

from the original sources and which are results of questionnaires, interviews, experiments,

tests, observations and other data gathering instruments. Data presented in tables and their

textual presentations are examples of findings. Findings do not directly answer the specific

questions asked at the beginning of the investigation or the explicit hypotheses but the

findings provide the bases for making the answers. Hence, the main functions of the

findings are to provide bases for making the conclusions.

Implication, inference, interpretation. These three terms are synonymous if not

exactly the same in meaning. They are used interchangeably. Each is a statements of the

possible meaning, probable causes and probable effects of a situation or condition as

revealed by the findings plus a veiled suggestion to continue the situation if it is good or to

adopt some remedial measures to eradicate or minimize its bad effects. Those who are to

be benefited and those who are going to suffer the bad effects should also be mentioned.

Implication, inference, or interpretation has at least four elements, namely,

condition, cause, effect, and continuance or remedial measure.

(1) Statement of the condition or situation. The condition or situation is

stated based upon the findings, whether satisfactory or unsatisfactory.

(2) Probable cause of the condition. Usually, also every condition has a

cause but, there must be also a logical and valid relationship between

the condition and its cause.

(3) Probable effects of the condition. Usually, also every condition has an

effect, either bad or good. However, there must also be a logical and

valid relationship between the condition and its effect and this must be

clearly given.

(4) A veiled suggestion for continuance or remedial measure, if the

possible effect is bad. If the effect of condition is good, then there

must be a hint for the continuance of the existence of the condition.

However, if the effect is deleterious there must be some suggestions

for the adoption of measures aimed at minimizing the harmful effects.

The interpretation of Table 1 and its textual presentation is as follows: All the science

teachers were qualified to teach in the high school as per regulation. Unfortunately, more

than half of them were not science majors and therefore cannot teach science. Taking all

other things equal, a teacher with a science major can teach better than one with a non-

science major. Consequently, it can be assumed that the teaching of science in the high

schools of Province A is weak. As a result, the students and the whole country will suffer

and the whole consequences will be far-reaching. There is a need to encourage the teachers

who are non-science majors to increase their science units by attending evening or summer

courses or by attending more science seminars.

Graphical Presentation of Data

A graph is a chart representing the quantitative variations or changes of a variable

itself, or quantitative changes of variable in comparison with those of another variable or

variables in pictorial or diagrammatic form.

The quantitative variations or changes in the data may refer to their qualitative,

geographical, or chronological attributes. For instance, if the number of teachers teaching

science in the high schools of Province A is graphed according to their degrees, the graphing

is qualitative; if their number is graphed according to their assignments in the towns where

the high schools are located, the graphing is geographical; and if their number is graphed

according to school year, the graphing is chronological.

Purpose of graphing. The purpose of graphing is to present the variations, changes,

and relationships of data in a most attractive, appealing, effective and convincing way.

Advantages of the graphic method. (Bacani, et al., pp. 54-55) According to Bacani,

et al. the following are the advantages of the graphical method:

1. It attracts attention more effectively than do tables, and, therefore, is

less likely to be overlooked. Readers may skip tables but pause to look

at charts.

2. The use of colors and pictorial diagrams makes a list of figures in

business reports more meaningful. (Also in thesis reports)

3. It gives a comprehensive view of quantitative data. The wandering of a

line exerts a more powerful effect in the reader’s mind than tabulated

data. It shows what is happening and what is likely to take place.

4. Graphs enable the busy executive of a business concern to grasp the

essential facts quickly and without much trouble. Any relation not seen

from the figures themselves is easily discovered from the graph.

Illustrations, including attractive charts and graphs, are now

considered by most businessmen as indispensable accompaniment to

good business reports.

5. Their general usefulness lies in the simplicity they add to the

presentation of numerical data.

Limitations of graphs. (Bacani, et al., pp. 55) If there are advantages there are also

disadvantages of the graph. Some of these are:

1. Graphs do not show as much information at a time as do tables.

2. Graphs do not show as much information at a time as do tables.

3. Charts require more skill, more time, and more expense to prepare

than tables.

4. Graphs cannot be quoted in the same way as tabulated data.

5. Graphs can be made only after the data have been tabulated.

Types of graphs or charts. Graphs may be classified into the following types:

1. Bar Graphs

a. Single vertical bar graph

b. Single horizontal bar graph

c. Grouped or multiple or composite bar graph

d. Duo-directional or bilateral bar graph

e. subdivided or component bar graph

f. Histogram

2. Linear Graphs

a. Time series or chronological line chart

b. Composite line chart

c. Frequency polygon

d. Ogive

e. band chart

3. Hundred per cent graphs or charts

a. Subdivided bar or rectangular bar graph

b. Circle or pie graph

4. Pictograms

5. Statistical maps

6. Ratio charts

Construction of individual graphs. Stated herein are the principles to be followed in

the construction of individual graphs.

1. The bar graph. The bar graph is often used for the graphic

presentation of data. It is generally used to make comparison of

simple magnitudes very much more clearly and more distinctly

perceptible to the eye. Each bar is drawn to a height or length equal to

the magnitude it represents as indicated in the scale (Y-axis). The bars

are separated from each other by a space equal to one-half the width

of a bar. However, there are no fixed rules that govern the

construction of graphs and the maker may only be guided by

aesthetic, proportional, and symmetrical considerations and for

convenience.

Comparison in bar graphs is linear. It is the length of each bar that determines the

size of a magnitude it represents and the relative position of that magnitude in a series of

like and related magnitudes.

a. The single vertical graph. In the single vertical graph, the bars are

constructed vertically and they portray the magnitudes of the

categories into which data have been classified. See figure 3 as an

example of bar graph. Vertical bars are usually used to depict time

series data.

b. Single horizontal bar graph. In this graph, the bars are constructed

horizontally and are used to compare magnitudes of the different

categories into which the data are classified. The horizontal bar graph

is usually used to compare magnitudes of categories.

Construction of graphs. In constructing graphs, two straight lines are drawn

perpendicular to each other, intersecting at a point called the point of origin and marked 0

(zero).

The horizontal line is called baseline, coordinate, or X-axis. It represents the

variables involved or the classes’ categories of the variable involved.

The vertical line is called ordinate or Y-axis. It represents the quantities of the

variables involved or the classes or categories of a variable involved. The Y-axis is divided

into unit distances with each unit distance represents 4,2 unit distances represent 8,3 unit

distances represents 12, etc. This is called the scale.

The distance measured to any point parallel to the X-axis from the Y-axis is called

the abscissa of the point and the distance of that point parallel to the Y-axis from the X-axis

is the ordinate of the point. The abscissa and the ordinate of a point are called the

coordinates of the point.

Plotting the graph means locating the meeting point of the abscissa and the ordinate.

Essentials of a graph. The essential parts of a graph are the following:

1. Number. Charts or graphs are also numbered for reference purposes.

The general is to write the number as Figure 1, Figure 2, Figure 3, etc.

at the bottom of the graph.

2. Title. The same price principles hold in graphs as in tables. The title is

usually written above the graph.

3. Scale. The scale indicates the length or height unit that represents a

certain amount of the variable which is the subject of the graph. The

scale enables the reader to interpret the significance of a number of

length or height units. Thus, if a length or height unit is equal to 2,

two lengths or height units’ equal 4, 3 length or height units equal to

6, etc. The Y-axis represents the scale.

4. Classification and arrangement. The principles of classification and

arrangement are the same in graphs as in tables.

5. Classes, categories, or time series are indicated at the X-axis and the

scale units are indicated at the Y-axis.

6. Symmetry of the graph. The whole chart or graph should be about

square; otherwise the length should be a little greater than the height.

The chart should be placed on the page in such a way that the margins

at the left and at the right should be about the same, or the margin at

the left is a little wider.

7. Footnote. The footnote, if there is any, should be placed immediately

below the graph aligned with the left side of the graph.

8. Source. The source of data, if there is any, should be written just

below the footnote, if there is any, but it should be above the graph

number.

An example of a vertical bar graph is figure 3, the data of which are taken from the

following table, Table 2.

Table 2

Enrollment of Pagasa High School

1985-1986 to 1989-1990

(By Curricular Year)

Curricular

Years

School Years

1989-1990 Total 1985-1986 1986-1987 1987-1988 1988-1989

F % F % F % F % F % F %

I 85 36 144 46 173 41 192 38 221 34 815 38

II 57 24 77 24 132 32 148 29 179 28 593 28

III 53 23 49 16 69 16 114 22 138 22 423 20

IV 40 17 45 14 46 11 56 11 102 16 289 14

Total 235 100 315 100 420 100 510 100 640 100 2120 100

Source: Principal’s Office

Enrollment of Pagasa High School

1985-1986 to 1989-1990

Number of

Students

1985-1986 1986-1987 1987-1988 1988-1989 1989-1990

Source: Principal’s Office

Figure 3

Example of a horizontal bar graph is Figure 4.

Enrolment of Pagasa High School

1989-1990

(By Curricular Year)

Curricular

Year

0 25 50 75 100 125 150 175 200 225

IV

III

II

I

Source: Principal’s Office

Figure 4

c. Grouped (Multiple or Composite) Bar graph. The grouped bar graph is used in

comparing two or more categories of a variable during a specified period or over successive

periods of time when the subgroups of the categories have common attributes. Figure 5

shows the comparison of the enrolments over five successive years of the curricular years of

the students of Pagasa High School, Table 2.

Enrolment of Pagasa High School

1985-1986 to 1989-1990

(By Curricular Year)

700

600

500

400

300

200

100

0

NumberoofoStudents

0

50

100

150

200

250

1985-'86 1986-'87 1987-'88 1988-'89 1989-'90

First year

Second year

Third year

Fourth year

Students

Source: Principal’s Office

Figure 5

d. Duo-directional or bilateral bar graph. This graph is used to present data in

the form of assets, profits, and positive numbers, liabilities, losses and

negative numbers. If the baseline is vertical, the bars at the left of the

baseline represents liabilities, losses or negative numbers and those at the

right side represent assets, profits, or positive numbers. If the baseline is

horizontal, the bars above it represent assets, profits, or positive number and

those below represents liabilities, losses, or negative numbers. An example of

a bilateral graph is Figure 6 which is derived from Table 3 just below.

Table 3

Financial Operations of Pagasa High School

1985-1986 to 1988-1989

(In Thousands of Pesos)

Results of

Operations

Earnings

Expenses

Profits

Loss

School Years

Total 1985-1986 1986-1987 1987-1988 1988-1989

310

450

470

600

1830

250

390

510

510

1660

60

60

90

210

40

40

Source: Treasurer’s Report

Profits and Loss of Pagasa High School

1985-1986 to 1988-1989

Thousands

Of Pesos

1985-1986 1986-1987 1987-1988 1988-1989

Source: Treasurer’s Report

Figure 6

e. Subdivided (or Component) bar graph. Subdivided bar graphs are used to

show the variations or changes of the component parts of a whole and the whole itself.

Cross-comparison of the proportionate distribution of the different parts can be made easily.

Figure 7 is an example of a subdivided bar graph showing the earnings, expenses, and

profits and loss of the Pagasa High School for a number of years.

90

60

30

0

-

30

-

60

-

90

Financial Operations of Pagasa High School

1985-1986 to 1988-1989

Thousands

Of Pesos

0

100

200

300

400

500

600

700

1985-1986 1986-1987 1987-1988 1988-1989

Earnings

Expenses

Profit

Loss

Source: Treasurer’s Report

Figure 7

f. Histogram. A histogram is composed of bars placed side by side whose

heights indicate the magnitudes of their respective classes or categories. It is

used with grouped or class frequency distributions. Figure 8 is an example.

The heights of the bar indicate the number of students in certain age groups.

Data are taken from Table 4.

Table 4

Age Distribution of Pagasa High School Students

School Year 1989-1990

Age Groups

Frequency

Cumulative

Frequency

Upward

Cumulative

Frequency

Downward

20-21

18-19

16-17

14-15

12-13

53

162

211

150

64

________

N = 640

640

587

425

214

64

53

215

426

576

640

Source: Principal’s Office

Age Distribution of Pagasa High School Students

School Year 1989-1990

Number of

Students

250

200

150

100

50

0

12-13 14-15 16-17 18-19 20-21

Age in Years

Source: Principal’s Office

Figure 8

2. Linear graphs. Linear graphs are good devices to show variations of values

over successive periods of time. Changes in the data are indicated by the linear curves.

Advantages of linear graphs or charts. The advantages of the linear graph or chart

are the following: (Bacani, et al., p. 67)

a. The curve shows data as continuous line; hence, it is continuous in its effect.

b. The wandering line of the curve tells the whole story. At a glance one can

see just what the situation is and what is likely to happen.

c. Its preparation requires less time and skill.

Construction. Linear graphs are constructed in much the same way as many other

graphs are. A slight difference lies in the process of locating the intersections of the abscissa

representing a class or category of a variable and the ordinate representing the magnitudes

of the classes or categories of the variable. The intersections of the abscissa and the

ordinate are marked by bold dots and then joined successively by either straight lines or

curved lines to show the variations of a variable or the variable in relation to that of

another.

a. Time series linear charts. (single line) Time series linear single line charts

depict the variations of a variable over a period of time. Generally, the abscissa represents

the periods of time and the Y-axis represents quantitative values of the variable. The

intersections of the X-axis representing time and the Y-axis representing magnitude are

located and marked and then joined successively by straight or curved lines. The resulting

line, a broken straight line or a curved line, shows the variations of the variable. An

example of this chart is Figure 9 which shows the enrolment of Pagasa High School for five

school years. See table 2 for exact data.

Enrolment of Pagasa High School

1985-1986 to 1989-1990

600

500

400

300

200

100

0

1985-1986 1986-1987 1987-1988 1988-1989 1989-1990

Source: Principal’s Office

Figure 9

b. Time series composite or multilinear charts. These charts are used when

comparisons are made between or among categories of the same variables or variations of

two or more variables over periods of time. Figure 10 is an example comparing the

enrolments of the curricular years over a period of five years in the Pagasa High School.

Exact data are found in Table 2.

Enrolment of Pagasa High School

1985-1986 to 1989-1990

(By Curricular Year)

Number of

Students

250

First Year

Second Year

Third Year

Fourth

Year

200

150

100

50

0

1985-1986 1986-1987 1987-1988 1988-1989 1989-1990

Source: Principal’s Office

Figure 10

c. Frequency polygon. The frequency polygon is used to graph class or grouped

frequency distributions. The X-axis represents the classes and the Y-axis represents the

frequencies of the classes. In plotting the interactions of the abscissas and ordinates, the

midpoints of the classes are used as abscissas. The linear curve starts from the midpoint of

the empty class just before the class with a frequency and ends at the midpoint of the

empty class just after the highest class with a frequency. Figure 11 is an example

presenting the age distributions of Pagasa High School students, school year 1989-1990.

The graph is based on data from Table 4.

Age Distribution of Pagasa High School Students

During the School Year 1989-1990

Number of

Students

250

200

150

100

50

0

12 14 16 18 20 22 24

Ages in Years

Source: Principal’s Office

Figure 11

d. The ogive. The ogive is used to graph cumulative frequencies (partial sums of

frequencies), either cumulative frequencies upward (from lower classes to

upper classes) or cumulative Frequencies downward (from upper classes to

lower classes). The items graphed may be absolute frequencies or derived

frequencies (percents). Figure 12 gives examples of ogives showing the

cumulative frequencies of students classified according to age. Data are taken

from Table 4.

Cumulative Frequencies of the Students of Pagasa High School

During the School Year 1989-1990

(Distribution by Age)

Number of

Students

700

600

500

Ogive

Upward

400

300

200

100

0

Ogive

Downward

12 14 16 18 20 22

Ages in Years

Source: Principal’s Office

Figure 12

e. Band Chart. A band chart is form of line graph of the time series variety. It

shows the proportional variations of the component parts of a whole over a

period of time. The percent equivalents of the components are the ones

plotted but absolute values may be used through rarely. The bands

representing the proportional changes may be colored or cross-hatched

differently to increase the clarity of the variations. Figure 13 is an example

which is based on data in Table 2. It shows the proportional or percent

changes of the students in the four curricular years.

In constructing the band chart, the largest component at the beginning of the period

is placed at the bottom, followed by the second largest component, etc. If percents are used

the band chart is a rectangle. If actual values are used, the upper line boundary of the chart

will be irregular.

Composition of Pagasa High School Students

1985-1986 to 1989-1990

(By Curricular Year)

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1985-1986 1986-1987 1987-1988 1988-1989 1989-1990

Axi

s Ti

tle Fourth year

Third year

Second year

First year

Source: Principal’s Office

Figure 13

3. One hundred percent graphs or charts. One hundred percent graphs or charts

show the comparison of the proportional sizes of the component parts that make up the

whole, the whole being made equivalent to 100%. It is the percent equivalent of the

component parts that are portrayed in the graph. The percent equivalent of each component

part is found by dividing it by the total of the component parts and multiplying the result by

100%. There are two types or kinds of 100% charts: a.) the 100% bar or rectangular chart

and b.) The pie chart or circle graph. These are to graph budgets, enrolments, sales, etc.

a. The 100% bar graph or rectangular chart. Usually, the bar graph is erected

vertically and the whole height is equivalent to 100%. The bar is subdivided

into segments whose number is equal to the number of component parts. The

size of each segment is proportional to the percent of the component part it

represents. The segments are arranged according to size with the largest

segment at the bottom. Each segment is labeled by the value and percent it

represents, the percent inside and the value outside. See example below,

Figure 14.

Suppose the following are the expenditures of the Pagasa High School

during the school year 1987-1988: (see Table 3)

Administration (Salaries) P 60,000.00 11.76%

Instruction (Salaries) P 310,000.00 60.79%

Facilities (Including building) P 100,000.00 19.61%

Miscellaneous P 40,000.00 7.84% Total P 510,000.00 100.00%

60.79%

19.61%

11.76%

7.84%

Expenditures of Pagasa High School

During the School Year 1987-1988

Miscellaneous

P40,000.00

Administration (Salaries)

P60,000.00

Facilities (Including Building)

P100,000.00

Instruction (Salaries)

P310,000.00

Source: Treasurer’s Report

Figure 14

b. The Pie Chart or circle Graph. The circle graphs has the same principles and

functions as the rectangular chart. It is also equated to 100% and because the circle has

3600, 1% is equated to 3.60 so that 60% must be equal to 2160 (3.6 x 60). Graphing again

the expenses of Pagasa High School in 1987-1988 using the circle graph, it is done as in

Figure 15 below.

Expenditures of Pagasa High School

During the School Year 1987-1988

7.84%

Source: Treasurer’s Report

Figure 15

11.76%

19.60% 60.79%

4. Pictograms. The pictogram or pictograph is used to portray data by means of

pictures or symbols. Since the pictogram cannot portray data accurately, its

only purpose is to make the comparison of magnitudes more vivid and clear.

Besides, it is very attractive and never fails to catch attention.

Construction. First, make a scale, that is, each picture or symbol must represent a

definite number of units. So, to find the number of pictures or symbols to represent a

magnitude, divide the magnitude by the number of units’ represented by each picture or

symbol. The pictures and symbols must be of the same size and arranged in a row of rows.

The symbols should suggest the nature of the subject matter of the data being presented.

For instance, an army may be presented by pictures of soldiers; population by pictures of

persons; Car registration by pictures of automobiles; money in circulation by pictures of

money bills or peso coins; etc. Figure 16 is an example showing the enrolment of Pagasa

High School from 1985-1986 to 1989-1990. The graph is based on Table 2.

Enrolment of Pagasa high School

1985-1986 to 1989-1990

1985-1986

1986-1987

1987-1988

1988-1989

1989-1990

Source: Principal’s Office, Table 2

Figure 16

Legend: = 50

Implications of the Findings

It is the general practice of thesis writers to discuss the summary of the implications

of their findings at the end of Chapter 4 or elsewhere in the thesis. From observations, it

appears that as far as research reporting is concerned, an implication consists of at least

five elements, namely:

1. The existence of a condition. This condition is a finding discovered in the

research. The condition may be favorable or unfavorable. If it is favorable, it

is strength of the subject studied. If it is unfavorable, it is a weakness of the

subject. For instance, in the study of the teaching of science in the high

schools of Province A, it is discovered that the majority of the science

teachers are not qualified to teach science. This finding is an unfavorable one

it is a weakness in the teaching of science.

2. The probable cause of the condition. If there is a condition there must be a

cause and there must be a logical relationship between the condition and the

cause, otherwise the cause may not be a valid one. In the example above,

the logical cause of the lack of enough qualified teachers to handle science

subjects is that either the people responsible for recruiting teachers were not

careful enough in the selection of teachers or there are not enough qualified

applicants for the positions of science teachers, or both.

3. The probable effect of the condition. Most likely, there is also a probable

effect of the condition and there must be a logical relationship between the

condition and its probable effect. The logical effect of the lack of enough

qualified teachers to teach science is that, taking all other things equal, the

science teachers in the high schools of Province A are not as effective as when

all the science teachers are fully qualified. It is understandable that a fully

qualified science teacher has more science knowledge and skills to impart to

his students than a non-qualified science teacher. Hence, the students would

suffer adversely.

4. The measure to remedy the unsatisfactory condition or to continue to

strengthen the favorable one. It is a natural reaction to institute a measure to

remedy an unfavorable situation. However, if a condition is found to be

favorable one it is also a natural reaction to continue it in operation and to

even further strengthen it. The logical step to take to remedy the unfavorable

situation is, if it is impractical to ease out the unqualified science teachers, to

enjoin or require them to improve their qualification by taking evening or

summer studies in science, by attending more science seminars, or by

increasing their readings in science especially those being published in science

journals, magazines, and other publications.

5. The entity or area involved or affected. In the example cited above, it is the

teaching of science in the high schools of Province A that is affected. Hence,

the topic for discussion must be entitled “Implications of the Findings to the

Teaching of Science.” Some researchers use the title “Implications to

Education” which is too broad and vague. The area directly affected by the

unfavorable or favorable conditions discovered in the study should be cited

more specifically.

Chapter 5 SUMMARY, CONCLUSIONS AND RECOMMENDATIONS

This is the last chapter of the thesis and the most important part because it is here

where the findings, and the whole thesis for that matter, are summarized; generalizations in

the form of conclusions are made; and the recommendations for the solution of problems

discovered in the study are addressed to those concerned.

Summary of Findings

Guidelines in writing the summary of findings. The following should be the

characteristics of the summary of findings:

1. There should be e brief statement about the main purpose of the study, the

population or respondents, the period of the study, method of research used,

the research instrument, and the sampling design. There should be no

explanations made.

Example. (Using the hypothetical study of teaching science in the high

schools of Province A). This study was conducted for the purpose of

determining the status of teaching science in the high schools of

Province A. The descriptive method of research was utilized and the

normative survey technique was used for gathering data. The

questionnaire served as the instrument for collecting data. All the

teachers handling science and a 20percent representative sample of

the students were the respondents. The inquiry was conducted during

the school year 1989-’90.

2. The findings may be lumped up all together but clarity demands that each

specific question under the statement of the problem must be written first to

followed by the findings that would answer it. The specific questions should

follow the order they are given under the statement of the problem.

Example. How qualified are the teachers handling science in the high

schools of province A?

Of the 59 teachers, 31 or 53.54 percent were BSE graduates and three

or 5.08 percent were MA degree holders. The rest, 25 or 42.37

percent, were non-BSE baccalaureate degree holders with at least 18

education units. Less than half of all the teachers, only 27 or 45.76

percent were science majors and the majority, 32 or 54.24 percent

were non-science majors.

3. The findings should be textual generalizations, that is, a summary of the

important data consisting of text and numbers. Every statement of fact

should consist of words, numbers, or statistical measures woven into a

meaningful statement. No deductions, nor inference, nor interpretation should

be made otherwise it will only be duplicated in the conclusion. See the

example in No. 2 just above.

4. Only the important findings, the highlights of the data, should be included in

the summary, especially those upon which the conclusions should be based.

5. Findings are not explained nor elaborated upon anymore. They should be

stated as concisely as possible.

6. No new data should be introduced in the summary of findings.

Conclusions

Guidelines in writing the conclusions. The following should be the characteristics of

the conclusions.

1. Conclusions are inferences, deductions, abstractions, implications,

interpretations, general statements, and/or generalizations based upon the

findings. Conclusions are the logical and valid outgrowths upon the findings.

They should not contain any numeral because numerals generally limit the

forceful effect or impact and scope of a generalization. No conclusions should

be made that are not based upon the findings.

Example: The conclusion that can be drawn from the findings in No. 2

under the summary of findings is this: All the teachers were qualified to teach

in the high school but the majority of them were not qualified to teach

science.

2. Conclusions should appropriately answer the specific questions raised at the

beginning of the investigation in the order they are given under the statement

of the problem. The study becomes almost meaningless if the questions

raised are not properly answered by the conclusions.

Example. If the question raised at the beginning of the research is:

“How adequate are the facilities for the teaching of science?” and the

findings show that the facilities are less than the needs of the

students, the answer and the conclusion should be: “The facilities for

the teaching of science are inadequate”.

3. Conclusions should point out what were factually learned from the inquiry.

However, no conclusions should be drawn from the implied or indirect effects

of the findings.

Example: From the findings that the majority of the teachers were

non-science majors and the facilities were less than the needs of the

students, what have been factually learned are that the majority of the

teachers were not qualified to teach science and the science facilities

were inadequate.

It cannot be concluded that science teaching in the high schools of

Province A was weak because there are no data telling that the science

instruction was weak. The weakness of science teaching is an indirect

or implied effect of the non-qualification of the teachers and the

inadequacy of the facilities. This is better placed under the summary of

implications.

If there is a specific question which runs this way “How strong science

instruction in the high schools of Province A as is perceived by the

teachers and students?”, then a conclusion to answer this question

should be drawn. However, the respondents should have been asked

how they perceived the degree of strength of the science instruction

whether it is very strong, strong, fairly strong, weak or very weak. The

conclusion should be based upon the responses to the question.

4. Conclusions should be formulated concisely, that is, brief and short, ye they

convey all the necessary information resulting from the study as required by

the specific questions.

5. Without any strong evidence to the contrary, conclusions should be stated

categorically. They should be worded as if they are 100 percent true and

correct. They should not give any hint that the researcher has some doubts

about their validity and reliability. The use of qualifiers such as probably,

perhaps, may be, and the like should be avoided as much as possible.

6. Conclusions should refer only to the population, area, or subject of the study.

Take for instance, the hypothetical teaching of science in the high schools of

Province A, all conclusions about the faculty, facilities, methods, problems,

etc. refer only to the teaching of science in the high schools of Province A.

7. Conclusions should not be repetitions of any statements anywhere in the

thesis. They may be recapitulations if necessary but they should be worded

differently and they should convey the same information as the statements

recapitulated.

Some Dangers to Avoid in Drawing up Conclusions Based on Quantitative Data

There are some pitfalls to avoid in the use of quantitative data. (Bacani, et al., pp.

48-52) researchers should not accept nor utilize quantitative data without questions or

analysis even if they are presented in authoritative-looking forms. This is so because in

some instances quantitative data are either inaccurate or misleading either unwittingly or by

design. The data should be analyzed very critically to avoid misleading interpretations and

conclusions. Among the factors that a researcher should guard against are the following:

1. Bias. Business establishments, agencies, or organizations usually present or

manipulate figures to their favor. For instance, an advertisement may quote

statistics to show that a given product is superior to any other leading brand.

We should be wary of the use of statistics in this case because of the obvious

profit motive behind. An individual may also do the same. A respondent to a

questionnaire or in an interview may commit the same bias o protect his own

interests. Like the case of the science teachers in the high schools of Province

A, they may respond that the science facilities in their respective schools are

adequate although they are not just to protect the good names of their own

schools. A respondent, if asked how many science books he has read, may

say that he has read many although he has read only a few to protect his

name. Hence, if there is a way of checking the veracity of presented data by

investigation, observation, or otherwise, this should be done to insure the

accuracy of the conclusion based upon the data under consideration.

2. Incorrect generalization. An incorrect generalization is made when there is a

limited body of information or when the sample is not representative of the

population. Take this case. The Alumni Association of a big university would

like to conduct a survey to determine the average income of the alumni

during their first ten years after graduation. Though the total number of

returns may meet the sample size requirement, the population may not be

properly represented by the actual composition of the sample. This is likely to

happen because chances are that a great majority of the alumni in the high

income bracket will respond readily but the great majority of those who are

not doing well may ignore the survey by reason of pride. In such a case, the

high income group is over represented and low income group is under

represented in the sample resulting in the overestimate of the average

income of the entire alumni group. This is the result of a built-in sampling

bias.

3. Incorrect deduction. This happens when a general rule is applied to a specific

case. Suppose there is a finding that the science facilities in the high schools

of Province A are inadequate. We cannot conclude at once that any particular

tool or equipment is definitely inadequate. Suppose there is an over-supply of

test tubes. Hence, to make the conclusions that all science equipment and

tools in the high schools of Province A are inadequate is an incorrect

deduction in this case.

4. Incorrect comparison. A basic error in statistical work is to compare two

things that are not really comparable. Again, let us go to high schools of

Province A. Suppose in the survey, School C has been found to have 20

microscopes and School D has only eight. We may conclude that School C is

better equipped with microscopes than School D. However, upon further

inquiry, School C has 1,500 students while School D has only 500 students.

Hence, the ratio in School C is 75 students is to one microscope while in

School D the ratio is 63 students is to one microscope. Hence, School D is

better equipped with microscopes than School C. to conclude that School C is

better equipped with microscopes than School D based on the number of

microscopes owned by each school is incorrect comparison.

5. Abuse of correlation data. A correlation study may show a high degree of

association between two variables. They may move in the same rate but it is

not right to conclude at once that one is the cause of the other unless

confirmed so by other studies. In no case does correlation show causal

relationship. When the government increases the price of gasoline, the prices

of commodities also starts to rise. We cannot conclude immediately that the

increase in price of gasoline is the sole cause of the increase in the prices of

commodities. There are other causes to consider such as shortage or

undersupply of the commodities, increased cost of production, panic buying,

etc. To be able to make a conclusive statement as to what is or what are the

real causes of the increases in prices of commodities, an intensive

investigation is needed.

6. Limited information furnished by any one ratio. A ratio shows only a partial

picture in most analytical work. Suppose the only information that we have

about a certain establishment is that the ratio does not show the kinds of

employees leaving and why they are leaving. We do not know whether the

losses of employees are caused by death, retirement, resignations, or

dismissals. We can only surmise but we cannot conclude with definiteness

that the causes of the 20% employee turnover are death, retirement, poor

working conditions, poor salary, etc. Avoid as much as possible making

conclusions not sufficiently and adequately supported by facts.

7. Misleading impression concerning magnitude of base variable. Ratios can give

erroneous impressions when they are used to express relationships between

two variables of small magnitudes. Take the following examples. A college

announced that 75% of its graduates passed he CPA examination at a certain

time. Another college also advertised that 100% of its graduates who took

that same examination passed. From these announcements we may form the

impression that the standard of instruction in the two colleges is high.

Actually only four graduates from the first college took the CPA licensing

examination and three happened to pass.

For recommending similar researches to be conducted, the recommendation should

be: It is recommended that similar researches should be conducted in other places. Other

provinces should also make inquiries into the status of the teaching of science in their own

high schools so that if similar problems and deficiencies are found, concerted efforts may be

exerted to improve science teaching in all high schools in the country.

Evaluation of a Thesis or Dissertation

Generally, a thesis or dissertation has to be defended before a panel of examiners

and then submitted to the proper authorities for acceptance as a piece of scholary work.

Hence, there should be some guidelines in evaluating a thesis or dissertation. The following

are offered to be the general criteria in judging the worthiness of a thesis or dissertation:

I. The subject and the Problems

1. Is the subject significant, timely and of current issue?

2. Is it clearly delimited but big enough for making valid generalizations?

3. Is the title appropriate for the subject?

4. Are the sub problems specific, clear, and unequivocal?

II. The Design of the Study

1. Is the research methodology appropriate?

2. Is the design clear and in accordance with the scientific method of research?

3. Is the report prepared carefully following acceptable format and mechanics?

4. Are the documentation adequate and properly done?

III. The Data (Findings)

1. Are the data adequate, valid and reliable?

2. Are they analyzed carefully and correctly treated statistically?

3. Are they interpreted correctly and adequately?

IV. Conclusions (Generalizations)

1. Are the conclusions based upon the findings?

2. Do they answer the specific questions raised at the beginning of the

investigation?

3. Are they logical and valid outcomes of the study?

4. Are they stated concisely and clearly and limited only to the subject of the

study?

V. Recommendations

1. Are the recommendations based upon the findings and conclusions?

2. Are they feasible, practical, and attainable?

3. Are they action-oriented? (They recommend action to remedy unfavorable

condition discovered)

4. Are they limited only to the subject of the study but recommend further

research on the same subject?

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