chapter 1 final

DATA AND INFORMATION

Unit 1Chapter-1

Data and Information

Introduction

By data, we mean known facts that can be recorded and that have implicit meaning. For example, consider the names, telephone numbers, and addresses of people you know. You must have recorded this data in an indexed address book, or on a diskette. This is a collection of data with some implicit meaning.

To solve any managerial problem that you face in the organisation you need relevant information. This relevant information has to meet the tests of sufficiency and accuracy to be useful to solve the problem in hand. This information, which is processed form of data, refers to collection of numbers, letters, or symbols, maintained or produced for the management when required.

Forms of Data

Data may be classified as:

(i) Primary Data

(ii) Secondary Data

Primary DataPrimary Data represents those items that are collected for the first time and first hand. The data is recorded as observed or encountered. Essentially, this data is the raw material and may be combined, or structured in any form. The point to be noted here is that the data has not been statistically processed. For example, data obtained by counting the number of bad pieces and good pieces in the production is the primary unprocessed data. After this the data can be statistically processed to yield the required information.

The main advantages of collecting primary data are the following:

(i) They are accurate and reliable as they are collected from the original source.

(ii) They provide detailed information according to requirements of the users.

(iii) It is more reliable and less prone to error.

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MANAGEMENT INFORMATION SYSTEMS

(iv) Definitions and meaning of terms used in data are explained to make it understandable and the process transparent.

(v) Method of collection, its limitations and other aspects are generally highlighted.

Where there are roses there will also be thorns. Following are the main limitations of the primary data:

(i) Cost: It is expensive to collect primary data.

(ii) Time: It is time consuming method of data collection.

(iii) Training: It requires experts/trained personnel to collect data.

Secondary DataThis is also known as published data. Data which is not originally collected but rather obtained from published sources and is normally statistically processed is known as secondary data. For example, data published by Reserve Bank of India, Ministry of Economic Affairs, Commerce Ministry as well as international bodies such as World Bank, Asian Development Bank, etc.

As is the case with primary data there are advantages and disadvantages associated with secondary data also. The advantages are:

(i) Cost: It is more economical than primary data, since data is already available.

(ii) Time: It is faster to collect and process as time has already been spent to collect the data.

(iii) Information insight: It provides a base on which further information can be collected to update it and finally use it. It provides valuable insights and contextual familiarity with the subject matter.

The limitations of secondary data are as follows:

(i) It may not be too relevant for the problem in hand as it was originally collected for some other context.

(ii) It could be outdated and hence not of much use in a dynamically changing environment.

(iii) The accuracy of secondary data as well as its reliability would depend on its source as the assumption made during the data collection are not specified.

(iv) Locating appropriate source and finally getting access to the data could be time consuming.

(v) The data available might be too extensive and a lot of time and money may be spent going through it.

Distinction between Primary Data and Secondary DataParameter Primary Data Secondary Data

Source of Data Original source Secondary sourceMethod of Data Collection

Observation method,Observation method,Questionnaire method, etc.

Published data from various sources

Statistical Processing Not Processed Usually processed

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Originality of DataOriginal.

Data collected by some

Original.First time collected by user

Not original. Data collected by some other agency

Use of Data Data is compiled for specific purposes

There may not be a specific purpose

Terms and Definitions of Units

Incorporated May not be incorporated

Copy of the Schedule Included ExcludedMethod of Data Collection Given May not be givenDescription of Sample Selection

Given May not be given

Time Required More LessCost to the Orgnaisation Expensive Comparatively cheaperEfforts Spent More LessAccuracy of Data More accurate Less accurateTraining Experts/trained people required Less trained required

On closer investigation, it will be noticed that the distinction between primary and secondary data in many cases is of degree only. Data, which would be secondary in the hands of one, could be primary for others. For example, to a bank the details of the customer are primary data, but to a reader of the report of the bank these details are secondary.

Chapter-2Generation of Data

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The procedure for generation or collection of data depends upon various considerations such as objective, scope, nature of investigation, etc. Availability of resources like money, time, manpower, etc., also affect the choice of a procedure. Data from a primary source are collected, for the first time, keeping in view the objective of investigation. Secondary data, on the other hand, are available from certain publications or reports. Such data are already collected by some other agency in the past for some other purpose. Thus, the primary data generated with a specified objective of investigation, are likely to be more reliable as compared to secondary data. The use of secondary data, whenever necessary, must be very carefully. The cost of generation of primary data, however, are much higher.

Data Capturing After the data has been generated, it should be captured or stored in a medium for its use in future.

Storage technology includes both the physical media for storing data, such as magnetic or optical desk or tape, and the software governing the organization of data on these physical media.

Collection of Primary DataConsiderations in Selection of Primary Data Study

While selecting the subject for primary data collection, the following considerations should be kept in mind:

(i) Economic Considerations

(a) Data collection efforts cost money. The value of the anticipated results must commensurate with the efforts put in.

(b) Short-term data collection studies that can yield appreciable dividends quickly should be preferred to long term studies whose benefits may be difficult to foresee.

(ii) Technical Considerations

(a) It should be made sure that adequate technical knowledge is available to carry out the right process of data collection.

(b) Where a large problem throws up a number of subjects which are independent of each other, it is better to have small individual data collected on each subject.

(c) Where a problem brings to light two or more subjects, which are interrelated, independent studies on each might be carried out in the preliminary stages, but they should later be continuously integrated by coordinating the recording of the different teams working on each subject. The critical examination has to be the completeness of the data and it has to be carried out by the team as a whole.

(d) The scope and magnitude of the problem would determine the data required

(iii) Human ConsiderationsWhere resistance to change or reaction is likely to be there the data collection should not be proceeded with until acceptance has been gained.

(iv) Other Limitations and Constraints(a) Time Limit: Data collection must be completed within time frame specified so as to be of

maximum utilisation.

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(b) Cost Considerations: Data must be collected within the cost framework .(c) Accuracy: Reasonable accuracy, as is required for the problem, should be ensured.

Methods of Primary Data Collection

The following four methods of primary data collection are most widely used:

1. Observation method

2. Personal interview

3. Questionnaire method

4. Case study method

Let us look at each method, one by one:

1. Observation Method

This is the most commonly used method of data collection, especially in studies relating to production management and behavioural sciences. Accurate watching and noting down of phenomena, as they occur in nature or at shopfloor with regard to cause and effect, is called the observation method of data collection.

Differentiating characteristics of observation method are as follows:

(i) Direct Method: Direct contacts of sensory organs particularly eyes and ears are involved to gather and record the data.

(ii) Observe and Record: The observer first observes the phenomenon carefully and then records data.

(iii) Selective and Purposeful Collection: The observations are made with a definite purpose in mind and only relevant data is collected.

(iv) Cause and Effect Relationship: Observation method leads to development cause and effect relationship.

Observation MethodMerits Limitations

This method of observation is common to all the discipline of research is simple to use.

It is realistic as it is based on actual and first hand experience.

The conclusions are more accurate reliable and dependable.

This method is used for formulation of hypothesis.

This method is successfully used for verification of hypothesis.

It is useful when indepth study is required.

Some events cannot be observed without biases. For example, it is not possible to observe emotions and sentimental factors, like and dislikes without bias about the degree of emotions.

It sometimes results in illusory observations. Being a long drawn process, the techniques of

observation are expensive and time consuming.

Sometimes the atmosphere tends to become artificial and this leads to a sense of self-consciousness among the individuals who are being observed. This defeats the purpose of observation.

The slowness of observation methods leads to disheartening and disinterest among both the

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observer and observed. The final results of observation depend upon

the interpretation and understanding of the observer, the defects of the subjectivity in the explanation creep in the description of the observed and deductions from it.

As the purpose of the observation is known to observers, therefore, it is his own wish to record or view a particular thing.

The control can be of two forms. The observer could be a participant or a silent observer. In group discussions he is normally a silent observer but in interview techniques he becomes a part of the interview and hence his lack of objectivity may hamper the quality of his observations.

Controlled and Uncontrolled Observation Methods are the two sub-methods used to watch and understand the observation.

(i) Controlled Observation: This is a systematic observation based on logic and reasoning. This is done on a preconceived plan and deliberate effort is made to control phenomena.

(ii) Uncontrolled Observation: In this method observations are made in a natural surrounding. There is no planning, no control and no use of any deliberate effort to change the working of the phenomenon.

Distinction between Controlled and Uncontrolled ObservationParameter Controlled Observation Uncontrolled Observation

Control Dimensions Control over the phenomenon, conditions of light, temperature, humidity, etc. Control over the observer or observed

No control. Observations under natural conditions

Techniques of Control Used

Planning of observations situations Use of mechanical appliances such as recorders, watch, etc.Maps and sociometric scalesHypothesisDetailed notesGroup discussions

No need to use control techniques

Degree of Bias Subjective study and bias comes in during study

This is an objective study and keeps the observations bias free

Cause and Effect Relationship

Well established Difficult to establish

Degree of Reliability of Data

High Low

The process of observation method is used most effectively in the field observations where the presence of the observer does not make a difference to the observed. For example, if you want to know how many people enter the New Delhi railway station from the Paharganj side, you just have to stand at the gate and count. Your presence there or not being there does not matter to people who are being observed.

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Steps in Organisation of Field Observation

Following are the main steps generally followed in the organisation of field observations:

(i) Determination of nature and limits of observation: Depending upon the nature of research and hypothesis, an outline of the research is prepared. This helps the observer to guide him on what should be observed and on what should be left out.

(ii) Determination of time, place and subject of study: A project can be short or of long duration, it may be studied under laboratory conditions or in the open. It should also be decided that whether we shall observe the behaviour of phenomenon as a whole or of the individual items in relation to the total.

(iii) Determination of the investigators: Depending on the nature, work content and objectives, the needs for individual investigator or of a team is to be identified.

(iv) Provision of mechanical appliances needed: The mechanical appliances for recording such as tape recorder, movie camera, etc. required should be identified in the beginning and used when needed.

When you take care of these basic steps, your data would be useful and relevant to the problem in hand.

2. Personal Interview Method

Under this method of collecting data there is a face to face contact with the persons from whom the information is to be obtained (known as informants). The interviewer asks them questions pertaining to the survey and collects the desired information. For example, if a person wants to collect data about the working conditions of the workers of Hindustan Lever Ltd, Mumbai, he would go to the HLL factory at Mumbai, contact the workers and obtain the required information. The information obtained is direct and original. This is the most suitable method of data collection for business and economic problems.

Personal Interview MethodMerits Demerits

In this method, direct contact between researcher and informants is established and effective communication is built, which helps in getting direct information about paradigms, inner feelings, emotions and sentiments.

Fine tuning of the responses can be done so as to get out the best possible by rephrasing the questions and probing deeper wherever required

There are certain matters, which can be written in privacy but about which one does not wish to speak before others. If these matters are the subjects of interview, the likelihood is that only a disguised version of these will be presented.

If an interviewee is of low level intelligence he is usually unfit to give correct information. Same goes for interviewer also as interviewing is an art rather than science and the art has to be mastered

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An interview gives us knowledge of facts, which are inaccessible to observation. The emotional attitude, secret motivation and incentives governing human life come to surface in an interview though these are unobservable. Therefore, interview has a quality which may be called supra-observational

Through this method it is possible to verify the information that has been collected from other sources.

If the interviewer is unable to suppress his prejudices, his understanding and interpretation of data given in the interview will be defective

In the interview, certain aspects of the human behaviour get overemphasized at the expense of others. There is a tendency to give too much importance to personal factors and minimise the role of environmental factors. This has to be guarded against.

Types of InterviewsInterviews can be classified according to their basic characteristics.

(i) According to formalness:

(a) Formal interview: In formal interviews, the interviewer presents a set of well defined questions and notes down the answers of informants in accordance with the prescribed rules. Here, emphasis is given on the order and on sequence of question.

(b) Informal Interview: Here the interviewer has the freedom of alterations in questions to suit a particular situation in formal interview. He may revise, reorder or rephrase the questions to suit the needs of the respondents. The emphasis is on situation and on questioning generally depends on the situation and on individual.

(ii) According to Number:

(a) Personal Interview: In personal interview only a single person is interviewed at one time. Detailed knowledge about intimate and personal aspects of individual can be obtained as it is fact-to-face talk.

(b) Group Interview: In this method two or more persons are interviewed at the same time. The group interview is, therefore, more suited for gathering routine information rather than personal information.

(iii) According to Purpose:

(a) Diagnostic Interview: In this type of interview, interviewer tries to understand the cause or causes because of which a particular fact or incident happened. For example, diagnostic interviews are held with the operators with a purpose to grasp the cause and nature of failure of machines and not to ascertain whether failure has occurred.

(b) Research Interview: These interviews are held to gather information pertaining to certain problems but may not be as specific as diagnostic interviews. The questions to be asked to gather the desired information are predetermined. In as much as this data is gathered for the purpose of research into a problem, these are called research interview.

(iv) On the basis of Function and Methodology:

(a) Non directed Interview (Non Directional Interview): This is also known as free or unstructured interview. This is a type of interview in which the interviewer exercises no control, provides no direction and has no brief or predetermined set of questions to ask. The interviewer merely engages the interviewee in talks and encourages him to tell about his experiences

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and feelings. This type of interview is suitable when the researcher wishes to assess the amount of awareness a person has about certain problems and the manner in which he views them.

(b) Focused Interview: This method is employed for studying the socio-psychological effects of mass media like radio, television, cinema, etc. The specialty of the focused interview is that by its means the personal reactions, emotions and intellectual orientation of the persons to be interviewed towards specific issues can be studied.

(v) Classification according to Subject Matter:

(a) Qualitative Interview: The qualitative interviews are about complex and non-quantifiable subject matter. For example, interviews held for case studies for specific problem study are qualitative, because the interviewer has to cover past, present and future to know a case. In this a qualitative analysis associated with a situation is performed. The subjective opinion of the interviewer is seeked.

(b) Quantitative Interview: The quantitative interviews are those in which certain set facts are gathered about large number of cases. The census interviews is an example of this type.

Many combinations of these types can be made to suit a particular situation.

Getting Correct Response in an Interview

The main concern of the researcher employing the method of interview is to get correct and to the point answers to the topic of research. A research can be less expensive and economical only if deviations from the main line of approach is kept under control. Normally, the accuracy of the responses depends upon the skill and tactful approach of the interviewer and no rules can be framed in this connection. Still the following points can be kept at the back of your mind:

Prior to start the business with the interviewee, interviewer must develop rapport with the interviewer, so that he feels comfortable with him.

For allowing maximum opportunity of self-expression to the interviewee, he should be allowed to narrate his experience in the story form.

The interviewee and interviewer should be free and frank. The interviewee should be allowed to describe whatever he thinks worthwhile. Even if some irrelevant facts are being described the interviewee need not be checked. He should not be discouraged. Though maximum freedom of self-expression is desirable, this can only be within the scope of the problem being discussed. This requires alertness and direction at the suitable occasion. Good humor is the essence of successful direction.

The interviewer must hear the interviewee with full interest. Nobody should be able to guess from his expression that he is bored or his mind is elsewhere.

If an interviewer can convince the interviewee that he appreciates his cooperation and greatly values the information's given by him, this word of encouragement has a salutary effect on the interviewee, who then gives more focused responses.

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The information given by the interviewee, if suspected, can be tested through cross-examination of the interviewee. Moreover, the emotional expression accompanying the responses give a clue to the interviewer about the veracity or otherwise of the answer being given.

Precautions to be taken while Interviewing

Following are the main causes, which render an interview unusable. These should be taken care of when interviewing:

(i) Often interviewees, under emotional spells, exaggerate the facts in order to satisfy their vanities and create impression. Should be taken with a pinch of salt.

(ii) Sometimes there is communication gap between the interviewer and interviewee with the result that interviewees say one thing and the interviewer understands something else.

(iii) Some interviewees deliberately try to mislead the interviewer and make a fool of him, the interviewer must be mature and experienced enough to tell off and rebuff such fake interviewees.

(iv) Sometimes an inexperienced interviewer is offended by the behaviour of interviewees and in a revengeful mood distorts the facts in his report.

(v) Interviewer should critically examine those aspects of the interview in which the relationship of cause and effect seems to hold. This helps to determine whether the causes are always present or not when certain effects appear.

3. Questionnaire Method

Under this method, a formal list of questions pertaining to the survey (known as questionnaire) is prepared and sent to the various informants. Questionnaire contains the questions and provides the space for answers. A request is made to the respondents through a covering letter to fill up the questionnaire and send it back within a specified time.

The questionnaires could be structured or unstructured. Structured questionnaires are those that pose definite, concrete and preordained questions with fixed response categories. In unstructured questionnaires, questions are not necessarily presented to the respondents in the same wording and do not have fixed responses. Respondents are free to answer the questions the way they like in their own wording and style. Questionnaires could be a mix of the two types also leaving the field wide open to the designer of the questionnaire.

Types of Questions Used in Devising a Questionnaire

Dichotomous Questions: When reply to a question is in the form of one out of two alternatives given, one answer being given in negative and other positive, it is called a dichotomous question. Both the negative and positive answers combined together form the whole range of answers given. For example: “Whether respondent is educated………………..Yes/No.”

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Multiple choice Questions: In these questions normally three to five alternative answers are given. These alternatives are quite comprehensive and the respondent has to select one of them. In framing these types of questions, the framer has to be cautious enough that all the possible alternatives are included in it and they are mutually exclusive.

Ranking item Questions: A variation on multiple choice questions, these questions are so designed as to record the preferences of the respondent. In ranking item questions there may be several preferences arranged item wise.

Open-ended Questions: Questions, which are of descriptive type and allow the respondent to cite his experiences are known as open-ended questions.

Leading Questions: These are suggestive questions. In these types of questions the reply is suggested in a particular direction. Should be avoided as far as possible.

Ambiguous Questions: The questions that lack clarity and are so worded that the meaning is not clear are known as ambiguous questions. Such questions normally should not be included in the questionnaire as they are likely to confuse the respondent. The meaning of such questions are not uniformly convulsed to all the respondents.

Questionnaire MethodMerits Demerits

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It requires less skill to administer than other methods

If the informants or the respondents are scattered in large geographical areas, this is the most suitable method

Besides saving money, time is also saved as simultaneously hundreds of persons can be approached

It is more reliable in special cases although in most cases the reliability is suspected

The respondent is free from external influences, such as researcher and therefore provides reliable, valid and meaningful information

Chances of errors are low because respondent supplies information himself

The informants are directly involved in the supply of information, so the method is more original

The impersonal nature of questionnaire ensures uniformity from one measurement situation to another.

Lack of interest on the part of respondents lowers the number of responses, making the study unreliable

Incomplete and illegible responses renders the whole response bad

If a problem requires deep and long study, it cannot be studied through this method

This method is very rigid since no alteration and rephrasing of questions can be used

Prejudices and bias of the researcher influences the framing of the questions

Sometimes the questionnaire is itself incomplete and leaves out certain critical questions which are unearthed later rendering the whole exercise fruitless

There is no provision in this method for coming face to face with the respondent. This may result in manipulation of replies by the respondents.

Considerations in Questionnaire Design

Questionnaire is always framed with the help of certain background material and the problem statement. The first requirement always is the design of the problem statement and this is the area where most of the questionnaires go wrong. If your problem statement is faulty, your questions are not going to point to the required direction and you are bound to get wrong inferences. Spend the maximum time on it, it will be well spent.

After the problem statement comes the issue of the respondents as their intellectual level has to be kept in mind while designing questions. If the questions, language and wordings are not in accordance with the intellectual level of respondents then it would not be possible for them to furnish correct replies. In such a situation the purpose of the research would not be fulfilled. The outcome of past experiences enables the researcher to know the shortcomings beforehand, enabling him to remove these deficiencies so as to improve the response rate.

Other factors to be taken into account in the construction of a questionnaire:

Appeal: Each questionnaire should be attached with an appeal in which the aim and purpose of the questionnaire is set forth and the sincere cooperation of the respondents is requested. The appeal may be made more effective by giving appropriate incentives in the form of money, books, and with a promise to give a copy of the report to the respondents.

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Instructions for filling up the questionnaire: The questionnaire must carry a list of instructions for filling it up and dispatching it. The respondent must not have to pay for return postage, unless you are promising a prize for responses. If the questionnaire is time bound, the last date of receiving completed response and the address should be clearly written.

Clarity of Questions: For desired response it is of utmost importance to formulate questions that are direct, clear and precise.

Order of Questions: The questions should be broken up into sections and each section should have a number of questions, which are mutually interrelated. Question about personal detail should be avoided or should be asked in the end.

Protesting of response in Questionnaire

The basic thing that has to be kept in mind is that ambiguity should be avoided in collecting data through questionnaire method. For this, it is necessary that the questionnaire should be tested before it is actually used in a business research study. Pre-testing is nothing but testing of questionnaire before it is actually used. If testing is to be done the right way the following steps are required:

Testing the validity in a representative sample: The questionnaire should be tested in every respect, before it is actually mailed to the target segment. This testing can be done on a limited number of people through sampling method but while testing it within the sample, it should not be forgotten that the sample should be perfectly representative of the target segment.

Pretesting to check whether the results are in tune with objectives: The questionnaire should meet the objective of research study. It means that it should help in getting maximum possible relevant responses. It is, therefore, necessary that it should be made suitable to objectives of study even if it requires testing more than once.

Poor response requires modification of the questionnaire: The questionnaire is mailed to the informants who are required to fill it and send it back. If the response of the informant is poor and very few questionnaires are returned, it means that there is something wrong with the form and style questionnaire and it requires modifications/change and reframing. Furthermore, if the questionnaires returned are incomplete or the replies are not satisfactory and up to the mark, it should be presumed that the questionnaire is defective and it requires modification. After modification the questionnaire should again be subjected to pretesting.

Problem of Response: Difficult Situations for the Researcher

When the questionnaire is not leading to any response, one of the following factors is usually responsible for it:

Importance of the problem to the respondents: It is generally seen that those who are concerned with the problem give better response than those who are not.

Characteristics of the respondents and prestige of the sponsoring body: It is seen that educated people with social consciousness are more responsive as compared to people belonging to lower economic group. If the research study is sponsored by a well-known organisation it is likely to have better response.

Form and nature of questionnaire and arrangements of the questions: Questionnaire also plays its part in the matter of response. If the questionnaire is short and has been printed in attractive manner, its layout is neat and attractive, the arrangements of questions is scientifically planned, it is likely to invite a better response.

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To get better response, inducement is needed. Inducement may be classified under two heads: monetary and non-monetary. Monetary inducement is given generally to people who are economically weak or likely to be influenced by money. This money is given in advance or after receiving the filled questionnaire. Non-monetary inducement may be in the form of a reward. It may be a letter of appreciation or mentioning of the name in the report of study and so on. The suitability of the inducement to the study and the respondent’s expectations has to be kept in mind when deciding upon which inducement to use.

To take care of the poor response situations companies normally get students to help to find respondents and to fillingup the questionnaires. Excellent way for you to make money while studying!

Schedule

Schedule is a variation of the questionnaire and can be defined as a Performa that contains a set of questions which are asked and filled by an interviewer himself in a face to face situation with interviewee. Unlike a questionnaire, the schedule acts as a guideline to the interviewer trying to get the required response from the interviewee. Schedule is a standardised device or a tool of observation to collect data in an objective manner. Same guidelines as mentioned in the questionnaire are to be kept in mind while making these schedules.

4. Case Study Method

Case study method may be defined as small, inclusive and intensive study of an situation in which investigator uses all his skills and methods for systematic gathering of enough information about a situation to understand the problem and its solution. The case study is a form of qualitative cum quantitative analysis involving the very careful and complete observation of a person, situation or institution.

Case Study Method

Merits Demerits

Intensive and deep study of the problem is possible

Study of subjective aspects of the problem is possible and more elaborative than other methods

Comparison of possible problem statements is easier

Valid hypothesis can be formulated and tested while the case is in development

Is very useful when you have to study processes and not isolated incidents

Very useful in situations where more of qualitative rather than quantitative decision making is involved.

Several unrealistic assumptions may be made when structuring the case, making it difficult to relax them later on

It is expensive in terms of money, time and energy

If there is improper understanding between the developer and the respondents, the data and hence the inferences could be false and misleading

Prejudices and biases come in more easily as the study is more subjective

It is not possible to apply sampling methods and generalisation often leads to false conclusions.

Collection of Secondary DataAlthough primary data is required for most of the internal business situations, many of the strategic decisions depend upon the information that is external to the organisation. The criticality of the decision and the time factor involved would decide whether secondary data is to be used or the situation calls for primary data.

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If the situation calls for secondary data, this data would normally be either published or unpublished. Unpublished records, although dealing with the matters of public interest, are not available to people in published form. It means that everybody cannot have access to these records. Proceedings of the meetings, noting on the files, private research, etc., form the category of unpublished records. Normally these records are very reliable since there is no fear of their being made public, the writers give out their views clearly.

Published records are available to people for investigation, perusal and for further use, survey reports, magazine articles, published studies, etc., fall under this category. The data contained in these documents can be considered reliable or unreliable depending upon the agency that is collecting the data and the sources it had used for collecting this data. Most of the information that is now available to people and researchers in regard to business environment are to be found in the form of reports. The reports published by governments are considered more dependable on one hand and on the other hand some people think that the reports that are published by certain private individuals and agencies are more dependable and reliable.

There are so many sources of published data that it is impossible to name them all here. Inspite of so many sources, the published data usually suffers from the following drawbacks:

(a) Data about all the aspects of business and economic activity are not collected.

(b) Even the Government of India does not have an up-to-date and latest data about many socio-economic aspects as well as the business environment, although it is now working towards it.

(c) Data lacks in homogeneity and continuity.

(d) The data collected by the government agencies is not beyond doubt. This is due to the approach of the administration and also because of the method of data collection. The resources that are put at the disposal of the machinery that is entrusted for the task of collection of data is very meagre.

(e) Data collected by private agencies run the risk of their biases coming into picture, as also their own aims and objectives could make them present the data in a improper way rendering it unuseful for you.

Therefore, before using the secondary data, it is essential that the investigator should satisfy himself that the data is: (a) Reliable, (b) Suitable, (c) Adequate and (d) Timely.

Reliability of data can be established by asking yourself the following questions: Who collected the data and from which sources? Are the methods used in collecting are standard methods and reliable? Whether both the compiler and source are dependable? The purpose for which the data were originally collected is in tune with the purpose that you are going to use the data for, the secondary data should be suitable for the purpose of enquiry. Even if the data is reliable it should not be used if the same is found to be unsuitable for the enquiry. For checking the suitability of data one should see: What was the object of the enquiry? The definitions of various items and units of collection must be carefully scrutinized. What was the accuracy aimed at? What is the time of collection of data required? Can it be regarded a normal time? Is the data homogeneous?

The secondary data may be reliable and suitable but the same may be inadequate for the purpose of investigation. The data collected earlier may refer to a problem area which could be narrower or wider than the area required for the present enquiry and if it is such, the data should be carefully scrutinized to test whether it meets the requirements or not. If it does not meet the requirements of the scope or the time frame of study, do not use the data just because it is the only data that is there. Although knowledge of the matter under consideration and proper use of the statistical methods is presupposed, great care is necessary in dealing with published statistics because of the limitations or inaccuracies that may be present.

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Chapter-3Editing of DataThe next logical step after the collection of data, is the process of refining it for proper utilization. This process is known as editing. Editing of data includes the identification and dropping of the unwanted information. In addition to this, certain steps are taken to complete the left out information. Another aim of editing is to find out and rectify possible errors or irregularities during the collection of data. Thus, the process of editing implies the scrutiny of data in various ways. The process of editing of primary data can be divided two the following six stages:

(i) Deciphering

(ii) Scrutiny for completeness

(iii) Scrutiny for uniformity

(iv) Scrutiny for consistency

(v) Scrutiny for accuracy

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(vi) Coding of data

In a similar way, the editing of secondary data implies its scrutiny relating to the following points:

(i) Are data representative?

(ii) Are data adequate?

(iii) Are data reliable?

Recording of DataRecording is the process of storing the available data into various homogeneous classes and subclasses according to some common characteristics or objective of investigation.

The data should be recorded in such a way that:

(i) A mass of data can be presented in a considered form.

(ii) The points of similarity and dissimilarity can be highlighted.

(iii) The relationship between variables can be understandable.

(iv) The comparison can be facilitated.

(v) The data can be prepared for tabulation and analysis.

(vi) Data and information can be stored in databases in data warehouses and in data marts.

Chapter-4Classification of DataThe collected data are a complex and unorganized mass of figures which is very difficult to analyse and interpret. Therefore, it becomes necessary to organize this so that it becomes easier to grasp its broad features. This task is accomplished by the process of classification and tabulation.

Requisites of a Good ClassificationA good classification must possess the following features :

1. Unambiguous : The classification should not lead to any ambiguity or confusion.

2. Exhaustive : A classification is said to be exhaustive if there is no item that cannot be allotted a class.

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3. Mutually Exclusive : Different classes are said to be mutually exclusive if they are non-overlapping. When a classification is mutually exclusive, each item of the data can be placed only in one of the classes.

4. Flexibility : A good classification should be capable of being adjusted according to the changed situations and conditions.

5. Stability : The principle of classification, once decided, should remain same throughout the analysis, otherwise it will not be possible to get meaningful results. In the absence of stability, the results of the same type of investigation at different time periods may not be comparable.

6. Suitability : The classification should be suitable to the objective(s) of investigation.

7. Homogeneity : A classification is said to be homogeneous if similar items are placed in a class.

8. Revealing : A classification is said to be revealing if it brings out essential features of the collected data. This can be done by selecting a suitable number of classes. Making few classes means over summarization while large number classes fail to reveal any pattern of behaviour of the variable.

Types of Classification

The nature of classification depends upon the purpose and objective of investigation. The following are some very common types of classification :

1. Geographical (or spatial) classification

2. Chronological classification

3. Conditional classification

4. Qualitative classification

5. Quantitative classification

1. Geographical (or spatial) classification

When the data are classified according to geographical location or region, it is called a geographical classification. For example, the Statewise Net Domestic Product for 1984-85 at current prices can be shown as below:

Statewise Net Domestic Product, 1984-85 (In Rs million, at current Prices)

1.AndhraPradesh2.Arunachal Pradesh3.Assam4.Bihar5.Gujrat6.Haryana7.Himachal Pradesh8. JammuandKashmir9.Karnataka10.Kerala11.MadhyaPradesh12.Maharashtra

116945160545544114140114434461211016113786879065713696500215545

13.Manipur14.Meghalaya15.Mizoram16.Nagaland17.Orissa18.Punjab19.Rajasthan20.Sikkim21.Tamil Nadu22.Tripura23.Uttar Pradesh24.WestBengal

3462270210262276474137439272862958

1116254376

213266150994

22


For the purpose of immediate location or comparison of the data, it is necessary that it should be presented either in alphabetical or in ascending (or descending) order of the figures.

2. Choronological classification

When the data are classified on the basis of its time of occurrence, it is called a chronological classification. Various time series such as ; National Income figures (annual), annual output of wheat, monthly expenditure of a household, daily consumption of milk, etc., are some examples of chronological classification.

3. Conditional classification

When the data are classified according to certain conditions, other than geographical or chronological, it is called a conditional classification. An example of such classification is given below :

Categorised Classification of Public Expenditure, 1986-87.

4. Qualitative classification or classification according to attributes

When the characteristics of the data are non-measurable, it is called a qualitative data. The examples of non-measurable characteristics are sex of a person, marital status, colour, honesty, intelligence, etc. These characteristics are also known as attributes. When qualitative data are given, various items can be classified into two or more groups according to a characteristic. If the data are classified only into two categories according to the presence or absence of an attribute, the classification is termed as dichotomous or twofold classification. On the other hand, if the data are classified into more than two categories according to an attribute, it is called a manifold classification. For example, classification of various students of a college according to the colour of their eyes like black, brown, gray, blue, etc. The conditional classification, given above, is also an example of a manifold classification.

If the classification is done according to a single attribute, it is known as a one-way classification. On the other hand, the classification done according to two or more attributes is known as a two-way classification. The example of a three-way classification, where population is dichotomized according to each attribute; sex, honesty and smoking habit, is given below :

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Category Amount(Rs Crores )

Share(Percentage)

1. General2. Defence3. Education4. Health5. Housing, Welfare and Social Security6. Economic Services7. Other Services

9464108541020225367002

32411902

12.914.813.93.59.5

44.21.2

Total 73371 100.0


We note that there will be eight subgroups of individuals like male, honest, smokers; male, honest, nonsmokers, etc.

In the classification, given above, the population is dichotomized with respect to each of the three attributes. There may be situations where classification with respect to one attribute is dichotomous while it is manifold with respect to the other. A two way classification of this type is shown as:

5. Quantitative classification or classification according to variables

In case of quantitative data, the characteristic is measurable in terms of numbers and is termed as variable, e.g., weight, height, income, the number of children in a family, the number of crime cases in a city, life of an electric bulb of a company, etc. A variable can take a different value corresponding to a different item of the population or universe.

Variables can be of two types (a) Discrete and (b) Continuous.

(a) Discrete Variable: A discrete variable can assume only some specific values in a given interval. For example, the number of children in a family, the number of rooms on each floor of a multistoried building, etc.

(b) Continuous Variable: A continuous variable can assume any value in a given interval. For example, monthly income of a worker can take any value, say, between Rs 1,000 to 2,500. The income of a worker can be Rs 1,500.25, etc. Similarly, the life of an electric bulb is a continuous variable that can take any value from 0 toIt must be pointed out here that, in practice, data collected on a continuous variable also look like the data of a discrete variable. This is due to the fact that measurements, done even with the finest degree of accuracy, can only be expressed in a discrete form. For example, height measured even with accuracy upto three places after decimal gives discrete values like 167.645 cms, 167.646 cms, etc. Similarly age, income, time, etc., are continuous variables but their actual measurements are expressed in terms of discrete numbers.In the classification according to variables, the data are classified by the values of the variables for each item. As in the case of attributes, the classification on the basis of a single variable is termed as a one-way classification. Similarly, there can be a two-way and multi-way classification of the data. For example, if the students of a class are classified on the basis of their marks in statistics, we get a one-way classification. However, if these students are simultaneously classified on the basis of marks in statistics and marks in economics, it becomes a two-way classification.It should be noted here that in a two-way classification, it is possible to have simultaneous classification according to an attribute and a variable. For example, the classification of students of a class on the basis of their marks in statistics and on the basis of the sex of the person.

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Retrieval of DataOnce the data has been recorded in a particular medium, it can be retrieved for its use in future. The main thing of consideration is that the retrieval of data is done to present complex and unwieldy facts in such a manner that they would be understandable, clear and comprehensible at a glance.

Presentation of DataThe data can be presented by following methods:a. Tabular Presentationb. Chartmatic Representation and

c. Graphic Representation

a) Tabular PresentationAlthough tabular presentation looks the easiest, in fact its structuring and formatting tells a lot about the emphasis that you wish to make. Relevant data presented in easily comparable form is the key to the effective presentation of data.

To give you an example, the following table represents the share market and important industries situation in the market. Compare this by presenting only the latest data and you understand how relevant using right fields in the table are for effective analysis requirements.Another way of presenting the data would be to give only the comparative figures of two periods and the let the reader draw his own inferences. The unstructured presentation and the structured presentation is given below of the budget statement, clearly highlighting the need for effective presentation. Simply by looking at the tables, you can tell which is structured and which is unstructured and that is the beauty of the presentation.

Share PricesLatest June

99Month Ago Year Ago Variation

MonthOver (%)

YearBSE Sensex 4,210 4,072 3,153 3.39 33.52Sensex shares P/E 17.11 16.5 12.69 3.70 34.83BSE National 1,806 1,756 1,385 2.85 30.40National shares P/E

15.8 15.45 11.39 2.27 38.72

ET Industry Indices-Engineering Goods

844 825 818 2.30 3.18

-Tyres & Tubes 3,885 3,920 3,886 -0.89 -0.03-Fertilisers & Chem

580 495 555 17.17 4.50

-Pharmaceuticals 4,147 4,536 2,006 -8.58 106.73-Plantations 1435 1445 1,107 -0.69 29.63All Indus./ All India 2,074 2,080 1,588 -0.29 30.60

Budget at a GlanceRs Billions

Item 1997-98 1998-89 1998-99 1999-2000

25


(Actual) (BE) (RE) (BE)1. Revenue Receipts 1,339 1,620 1,577 1,8282. Tax Revenue (Net to Centre)

957 1,169 1,095 1,324

3. Non-tax Revenue 382 451 481 5054. Capital Receipts 982 1,059 1,242 1,0105. Recoveries of loans 83 99 115 1116. Other Receipts 9 50 90 1007. Borrowings and other liabilities

910799

889 910 1,037 799

8. Total Receipts 2,321 2,679 2,819 2,8399. Non-plan Expenditure 1,730 1,959 2,135 2,06910. On Revenue Account 1,453 1,663 1,767 1,90311. Interest Payments 656 750 772 88012. On Capital Account 278 296 368 16513. Plan Expenditure 591 720 684 77014. On Revenue Account 352 438 414 46615. On Capital Account 239 282 269 30316. Total Expenditure (9+13) 2,321 2,679 2,819 2,83917. Revenue Expenditure (10+14)

1,803 2,101 2,181 2,370

18. Capital Expenditure (12+15)

517 579 638 469

19. Revenue Deficit (1-17) 464 481 605 54120. Fiscal Deficit (1+5+6)-16 889 910 1,037 79921. Primary Deficit (20-11) 233 160 265 -80

(b) Chartmatic RepresentationTables are required but in themselves are not sufficient for the proper presentation of data. Charts and curves are also very useful aids for data presentation. The special features of charts are that they do away with figures altogether and present attractive, simple and appealing pictures and charts. Figures are usually avoided by manager and common man alike but pictures, charts and graphs, etc., always attract and impress them. A page from the budget report will make cold and uninteresting reading, but when it is translated into the language of charts and graphs it becomes fascinating. This is much more so with the advent of multimedia technology. For example, it would be sufficient to show the following from the Union Budget 1999.

Rupee Comes From

26


The above graph is called a pie chart. See how much user-friendly it is to look at. Contrast this with the table given below which shows the same figures in a tabular form.

Borrowings & Other

Liabilities

Corporation Tax

Income Tax

Customs

Excise

Other Taxes

Non-Tax Revenue

Non-Debt Capital receipts

Rupee Comes From

25 9 8 15 20 2 15 6

As is the case with other methods, chartmatic presentation also has its own merits and demerits:

Chartmatic PresentationMerits Demerits

Easy to Understand: They give a bird’s eye view of the entire data and therefore the contents/ information presented is easily understood.

Economy of Time and Labour: Since little effort is necessary in understanding charts they save time which is otherwise needed in drawing inferences from a set of figures.

Simplification of Complexity: Charts simplify complexities of statistical data. Generally all figures and particularly big ones are not easily understood, but if they are presented using charts their importance is at once realised.

Lasting Impression: The impression created by charts is more lasting than the effect of a set of figures. They have a great memorising effect.

Helpful in Comparison: Charts make comparison easy. With the help of charts comparisons of groups, and series of figures can be made with very little trouble.

Useful to All: Charts have universal usefulness. They are useful to all users, whether they are social scientists, mathematicians, businessmen, economists, engineers or statisticians.

Only Comparison is Possible: One of the greatest merit of chart is that it facilitates comparison. But only when one chart is available, this purpose stands defeated.

Approximate Picture of Data: Charts cannot be used everywhere to represent data, because they provide only approximate picture of data.

Difficult to Show Minor Differences: Through charts it is not possible to show minor differences.

Limited Information: Charts are useful only for general uses as they provide only limited information.

Correct Conclusions are not Possible: Through charts, it is difficult to have correct conclusions. They show only approximate values.

Easily Misused: Charts are capable of being misused very easily. If a wrong type of chart is used it can give fallacious conclusions and one should always safeguard against such types of charts and pictures.

Charts are not capable of further mathematical treatment.

The two dimensional and three dimensional charts cannot be accurately appraised visually and therefore, as far as possible, their use should be avoided.

Basic Design PrinciplesFactors to be considered in designing a chart

27


The following are the main basic principles that should be used in the design and layout of charts:

(i) Nature of Data: It is a fact which one should recognize that certain type of data do not lend themselves to satisfactory chartmatic or graphic presentation. Thus, it is advisable not to attempt to construct a chart or chart that would possess no advantage over the original data.

(ii) Purpose of the Chart: Chart or charts of all types should fulfill the following objectives.

(a) The chart should be accurate representative of data.

(b) The chart should be clear, easily read and understood.

(c) The chart should be constructed as to attract and hold attention.

(iii) Time Available for Preparation: Time and labour involved, in the construction of charts are of great importance. Designing a chart should never be hurried. If the amount of time is inadequate, every effort should be made to simplify and expedite the work, but not at the cost of lowering standards.

(iv) End-user: The educational standard and interest of end-user for whom the chart is meant should be given primary consideration.

One-Dimensional Charts or Bar Charts

Bar charts are in the shape of vertical or horizontal lines or bars. Length of the line or bar is proportional to the different figures they represent. They are called one dimensional because it is only the length of the bar that matters. Bar charts are the easiest and most adaptable general purpose charts. But they should be used only to represent small amounts of data which is in one series.

The following chart represents the inflation rate for the last one year using bar chart:

Inflation Rate

Here each bar represents one month. Note that writing the exact percentage of inflation over each bar makes it easier for you to know the exact percentage.

Selection of Suitable ChartsThere are many chart types which can be used as required. Seven most used ones, are given below. The data table being used for most of the graphs is this one:

Four Quarter Sales from three regions for Vibhu Industries 1st Qtr 2nd Qtr 3rd Qtr 4th Qtr

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7.418.04

8.78 8.67 8.22 7.85

5.534.43

5.26 5.124.2 3.9 3.53

3.004.005.006.007.008.009.00

10.00

June July Aug Sep Oct Nov Dec Jan Feb Mar Apr May June

(%)


East 20.4 27.4 90 20.4West 30.6 38.6 34.6 31.6North 45.9 46.9 45 43.9

1. Line Chart

These show trends or changes in data over a period of time, at even intervals. Although similar to an area chart, a line chart emphasizes time flow and rate of change, rather than the amount of change.When you need to show trends or changes in data at uneven or clustered intervals, an xy (scatter) chart is usually more appropriate than a line chart.High-Low-Close and Open-High-Low-Close Charts: The high-low-close and open-high-low-close subtypes of a line chart are often used for stock prices; the open-high-low-close subtype is sometimes called a candlestick chart. The high-low-close chart subtype can also be used for scientific data, for example, to indicate temperature changes.

2. Area Chart

It shows the relative importance of values over a period of time. Although similar to a line chart, an area chart emphasizes the amount of change (magnitude of values) rather than time and the rate of change.

3. Bar Chart

29

0

20

4060

80

100

1st Qtr 2nd Qtr 3rd Qtr 4th Qtr

EastWestNorth

0

50

100

150

200

1st Qtr 2nd Qtr 3rd Qtr 4th Qtr

NorthWestEast

0 20 40 60 80 100

1st Qtr

2nd Qtr

3rd Qtr

4th Qtr

NorthWestEast


It shows individual figures at a specific time or illustrates comparisons between items. The stacked and 100% stacked subtypes show relationships to a whole. The categories on a bar chart are organised vertically, the values horizontally, placing more emphasis on comparisons and less emphasis on time. Example of a 100% stacked subtype is shown below:

Note that it shows the relative share of each zone in each of the quarters making it easier to decipher how the market shares are moving.

4. Column Chart

It shows variation over a period of time or illustrates comparisons between items. The stacked and 100% stacked subtypes show relationships to a whole. Although similar to a bar chart, a column chart’s categories are organised horizontally, its values vertically.

5. Pie Chart

It shows the proportions of parts to a whole. This chart type is useful for emphasizing a significant element. A pie chart always contains one data series; if you have more than one data series selected, only one will be displayed in your chart. An example has already been shown before. If you want to show more than one data series use doughnut charts as shown below.

6. Doughnut Chart

30

0% 20% 40% 60% 80% 100%

1st Qtr

2nd Qtr

3rd Qtr

4th Qtr

EastWestNorth

020406080

100

1st Qtr 2ndQtr

3rd Qtr4th Qtr

EastWestNorth

1st Qtr2nd Qtr3rd Qtr4th Qtr

Outer circlerepresents north,middle onerepresents west andinner onerepresents east


Like the pie chart, doughnut chart shows the proportions of parts to a whole. The main difference, other than the “doughnut hole,” is that it can show more than one data series, unlike the pie chart. The doughnut chart is widely used in Asian countries.

7. Radar chart

It shows changes or frequencies of data series relative to a centre point and to one another. Each category has its own value axis radiating from the centre point; lines connect all the data markers in the same series. The radar chart is widely used in Asian countries.

(c) Graphic RepresentationAlthough charts are all right for presentation purposes, for statistical analysis purposes we need to have continuous charts which make it easy for us to analyse data. Obviously time series and frequency distributions cannot be reliably plotted on the charts hence the need for graphs. Graphs render a complex data simple and more easily understandable and also make comparison easy by bringing connected data near each other and placing their graphic representation side by side.

When to Use and not to Use Graphs

The graphs may be used in the following circumstances:

(i) When the emphasis is on the movement rather than on the actual amount.

(ii) When several series have to be compared only cursorily.

(iii) When figures cover a long period of time.

(iv) When a frequency distribution is represented by two or more curves.

31

050

1001st Qtr

2nd Qtr

3rd Qtr

4th QtrEastWestNorth


(v) When estimates, forecasts, interpolation, or extrapolation are to be shown.

The graphs may not be used in the following cases:

(i) Where there are very few plotted values in the series.

(ii) When the emphasis should be on the change in amounts rather than on the movement of the series.

(iii) To emphasize the difference between values or amounts on different dates.

(iv) When the movement of data is extremely irregular.

(v) When the presentation is designed for popular appeal.

The graphs are divided into two categories: (i) Graphs of Time Series or Histograms, (ii) Graphs of Frequency Distribution.

Although the graphs are usually made on the natural scale, it is difficult to draw interpretations from when the relative rates of change are to be studied. In these cases we make use of the logarithmic or the ratio scale. In ratio scale equal vertical distances indicate equal relative rates of change or equal percentage change. This scale is mostly used while studying the changes in sales, profits, production, etc.

Log graphs use log scales on both the axis and semi-log graphs use an arithmetic scale on the horizontal axis. When plotted on logarithmic paper, a geometric progression forms a straight line since logarithms of a geometric progression form an arithmetic progression.

Interpretation of Semi-logarithmic Graphs

The following may be considered as the rules for the interpretation of the semi-logarithmic curves: A curve increasing at a constant rate takes the form of a straight ascending line, while a curve

decreasing at a uniform rate is a straight descending line. An ascending convex curve indicates an increase at a decreasing rate, i.e., if the curve bends upward

the rate of growth is increasing. If the curve bends downward the rate of growth is decreasing.

A curve increasing at an increasing growth rate moves upward in concave fashion. If the curve is decreasing at an increasing rate the curve pattern is convex downward.

When the curve is horizontal, it is neither increasing nor decreasing. If the direction of the curve in one portion is the same as in another portion, it indicates the same percentage rate of change in both.

If two curves on the same ratio graph run parallel they represent equal percentage rates of changes. If the curve is steeper in one portion than another, it indicates a more rapid rate of change in the former than in the later.

Difference between Natural Scale and Log Scale

In a natural scale, equal differences are measured by equal distances, thus absolute movements are studied. In a log scale, however, the difference between scale measures equal proportional movement. This is clear from the following illustration:

32


Arithmetic Progression(adding z to last number)

Geometric Progression(doubling the last number)

2 24 46 88 16

10 3212 6414 128

The natural scale is based on the arithmetic progression while ratio scale is based on the geometric progression. Natural scale indicates absolute change whereas ratio scale indicates rate of change or relative changes. Negative values can be shown on the natural scale but not on the ratio scale. In natural scale simple graph paper is used, whereas in the ratio scale semi logarithmic graph paper is used. In case of ratio scales the meaning of the data is derived from the direction of line whereas in the case of natural scale the meaning is derived from the position of line. In case of variables having wide range of values, ratio scale is preferred over natural scale. In the natural scale, the measurement starts from zero on the vertical scale and sometimes false base line is used, but in ratio scale the measurement on vertical axis does not start with zero, hence it does not require false base line.

HistogramThe word historigram should not be confused with histogram. Graphs of continuous time series are known as historigram. If absolute values of a variable are taken into consideration the graph obtained by plotting them is known as absolute historigram. If the values are represented by index numbers and if in place of actual values indices of index numbers are plotted, the graphs so obtained are called index historigrams. Historgrams may be constructed on the natural scale or on ratio scales.

In a histogram the data are plotted as a series of rectangles. Class intervals are shown on the x axis and the frequencies on the y axis. There are as many columns as there are classes. The height of each rectangle represents the corresponding frequency of that class. Each rectangle is joined with the other. This gives a continuous picture. The sum of frequencies is represented by the total area of the histogram, while the area of various columns is proportional to the frequencies of the respective classes.

The histogram is especially appropriate for depicting continuous series, although it is also used for discrete series. One disadvantage of histogram is that different groupings would give different shapes.

Column charts and histograms are different from each other. In a histogram, the bars are adjacent to one another, which is not so in other column charts. The area of the bar is proportional to the frequency and not only the height. But in case of column charts this condition is not necessary. Finally, histogram represents continuous data but column charts cannot represent continuous data.

The table for which the histogram shown below is made, is given below:

Daily Wages (Rs.) No. of Workers Daily Wages (Rs.) No. of Workers20-25 21 55-60 6825-30 29 60-65 6030-35 34 65-70 5035-40 39 70-75 43

33


40-45 43 75-80 3945-50 50 80-85 3450-55 60 85-90 29

90-95 21

We can plot these points using a line and the graph that results due to it is called the frequency polygon. We are showing it in two ways, one way is plotted on the frequency distribution and the second way is standalone.

Frequency Histogram of wages of factory workers

Frequency Polygon of wages of factory workers

Of course this curve can be somoothened to get the frequency curve which is used in most of the probability distributions.

Frequency Distribution of wages of factory workers

34

01020304050607080

20-2

5

30-3

5

40-4

5

50-5

5

60-6

5

70-7

5

80-8

5

90-9

5

Number of Workers

01020304050607080

20-2

5

30-3

5

40-4

5

50-5

5

60-6

5

70-7

5

80-8

5

90-9

5

0

20

40

60

80

20-2

5

30-3

5

40-4

5

50-5

5

60-6

5

70-7

5

80-8

5

90-9

5

Number of Workers


Processing of Data

Business do not run on just raw data. They run on information (Data, when processed and presented in proper context, becomes information which controls the activity of the organization) and the knowledge of how to put that information to use. Knowledge is not readily available, however, especially in today's world. In many cases it is continuously constructed from data and/or information, in a process that may not be simple or easy.

SummarySo after going through this chapter, we can summarize the concepts.

Data is the known facts that can be recorded and that have implicit meaning.

Primary data represents those items that are collected for the first time and first hand.

Secondary data is the data which is not originally collected but rather obtained from published sources and is normally statistically processed.

Accurate watching and noting down of phenomena, as they occur in nature or at shopfloor with regard to cause and effect, is called the observation method of data collection.

Under Personal Interview Method of collecting data there is a face-to-face contact with the informants.

Under questionnaire method, a formal list of questions pertaining to the survey is prepared and sent to the various informants.

In case of quantitative data, the characteristic is measurable in terms of numbers and is termed as variable.

Editing of data includes the identification and dropping of the unwanted information.

Recording of data is the process of storing the available data into various homogeneous classes and subclasses according to some common characteristics or objective of investigation.

Once the data has been recorded in a particular medium, it can be retrieved for its use in future.

35


Knowledge is continuously constructed from data and/or information, in a process that may not be simple or easy.

36

chapter 1 final

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