research final exam

7/30/2019 Research Final Exam

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Gerald Giuliano

HWC 511 Research I

Final ExamProfessor Robert Marmo

1. There are at least foue levels of measurement: ratio, ordinal, nominal, and

interval. The differences amongst these four variables are that the four levels can

be seen from lowest to greatest or highest precision which is in the order of

nominal, ordinal, interval, and ratio. Each level gives a particular type of

information. For instance, nominal variables show that there is only a difference

among the groups being studied. An example of nominal variable would thus be

gender, ethnicity, or race. Therefore an ordinal measure would indicate a

difference plus it can be ranked or ordered. An example of this would be polling a

group of individuals their opinion on the death penalty from strongly favorable,

favorable, not favorable, and strongly unfavorable. The third level is an interval

measure which again be made up of different categories, can be ranked, but also

indicates the distance between these categories. Thus, an example would be SAT

scores or anything that can be weighed by increase in volume, etc. Lastly, is the

ratio measure which differs from the other measurements in that it marks all four

traits of measurement, it has to be of a different category, be in ranked order, have

a distance between the groups being measured and have a true zero, a true zero is

rarely found in social work studies, but is exampled by age which has a true zero

at a persons birth (i.e. 0), or money as a good example, for instance 0 to 1000

dollars.


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2. The true reliability of a measure can never be established or perfected, though

there are many ways a researcher could improve or increase the reliability of their

measure. This can be done by meeting 4 criteria which are clearly conceptualizing

all concepts, use a precise level of measurement, use multiple indicators of a

variable, and usage of pilot tests. First by clearly giving an operational definition

of concepts removing any ambiguity such as information found in other

constructs. Then, use a precise level of measurement by using indicators that hold

more specific information such as looking at the different between those who

make 20,000 dollars a year from those who make 200,000 a year from there, the

researcher would be able to say that someone making 20,000 a year is less likely

to have health insurance, etc. Then use multiple indicators of a variable such as

low student attendance then within this variable, two indicators come about low

student attendance due to illness, or low student attendance due to criminal-

related behavior. Lastly, the investigator can do pretests, by looking at previous

studies to build on the measure you are looking at currently.

3. A sampling frame is a list of cases in a population, or the best estimate of it. It is

seen as being important to the researcher because it is critical to good sampling. If

the researcher fails to take this into account, there will be a disparity between

theoretical and operational definitions of a variable creates inaccurate

measurement thus leading to invalid sampling.


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4. Researchers settle on the size of a given sample depending upon the kind of data

analysis the researcher is planning to use, on the populations traits, and on how

accurate the sample is needed to be for the researchers purpose. The researcher

thus finds that the smaller the population, the larger the sampling ratio has to be

for an accurate sample.

5. There are both advantages and disadvantages of open-ended versus closed-ended

questions in a survey. The advantages of closed-end questions are easier/quicker

for respondents to answer, the answers of different respondents are easier to

compare, answers easier to code and statistically analyze, response choices can

clarify question meaning for respondents, those surveyed are more likely to

answer about sensitive subjects, fewer irrelevant, or confused answers to

questions, less articulate or less literate people aren't at a disadvantage, and lastly

replication is easier. The disadvantages of closed questions are that they suggest

ideas that the subjects would not otherwise have, respondents without an opinion

or knowledge can answer survey, subjects can become frustrated because their

desired answer is not a choice, becomes confusing if there are 10 or more choices

in response to question, a misinterpreted question can go unnoticed, distinctions

between respondent answers may be blurred, mistakes or marking the wrong

answer is possible, it forces people to give simplistic responses to complex issues,

and forces people to make choices they would never make in real world settings.

As for open-ended questions, the advantages are they permit an unlimited number

of possible responses, test-takers can answer in detail and can clarify their


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answers, unanticipated findings can be discovered, permit adequate answers to

complex issues, permit richness of detail, and reveal answerers process of logic.

But the disadvantages of open-ended questions are that different test-takers give

different degrees of detail, responses can be irrelevant, comparison and statistical

analysis becomes difficult, articulate subjects are at an advantage, coping

responses are difficult, questions maybe too general, responses are written

verbatim which is difficult for interviewers, a greater amount of time, thought,

and effort is necessary, and test-takers can be intimidated by the process. Overall,

closed-ended questions are good for studies that are looking for at numbers where

you can find more reliability that the study reflects a larger audience than the

number of participants in a given study. Then again, close-ended questions lead to

lessen the possibility that a long-winded answer might yield new hypothesis for

further testing, which is then the advantage of open-ended questions. But then you

run the risk that the questions become too vague and the respondent going in all

different directions.

6. Ordinary conversation differs from survey interviews, in that survey interviews

are more structured, and have a more concrete purpose. An ordinary conversation

also leads to less of a question and answer format with the interviewer taking the

lead in moving the survey interview to the issue at hand, but is more casual and a

partnership of equals, and less likely to have a judgmental response from the

interviewer than say from a friend good or bad.


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7. A researcher must be aware of the problems in reliability when using existing

and/or secondary statistical data because the data in of itself could be tainted or

biased. But common error ends up being the fallacy of misplaced concreteness

which happens when someone gives a false impression of accuracy by quoting

statistics in greater detail than is warranted by how the statistics are collected, in

order to impress the audience of ones command of the subject matter.

Furthermore, problems of reliability arise in three areas: stability reliability,

equivalence reliability, and representative reliability. Stability reliability causes

problems when official definitions or technique of collecting information changes

over time as in the fact that in the coming years paper questionnaires might

become obsolete and will be digitalized. Then with equivalence reliability there is

the issue of using data that comes from across different parts of the country might

reveal data that found in one city was kept in an orderly fashion whereas another

city showed poor management of the data, thus making the statistics less reliable.

Lastly, there is representative reliability to be taken in account which is, such as

finding data that supported an increase in unemployment for females in New

Mexico because it was presumed that they were home-makers thus seemingly the

researchers had data that seemed to show that the demographics of Spanish-

speaking residents showed a lack of interest in finding employment opportunities.

8. There are advantages and disadvantages of secondary data analysis in research.

The advantages to secondary data analysis is that its relatively cheaper and faster

than doing an original study, you gain the benefit of using research from experts


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in the field adding to quality data, with limited time and resources, you gain the

advantage of sampling from large populations such as state or national level. But

then you must take into account that the disadvantages of secondary data analysis

is that you cannot delineate sample of national populations and narrow them down

to studying a subgroup such as transsexual drug addicts living in New York City.

Secondary analysis can be manipulated to fit the researchers purposes, and most

research of large sampling involves large, cumbersome data files.

9. The elements of a classical experimental design are that it has a control group, an

experimental group, a pretest and posttest, and random assignment. Thus, a

researcher looking into the side effects of an antidepressant, would take say 200

willing participants and then random divide them into two groups, one control and

one experimental. The control group is then the group that would not get the

treatment and then there is an experimental group that would get the treatment

(i.e. drug). The researchers would then give the participants pretests and then after

an allotted interval after the text, a post-test to measure the effects if any.

10. A double blind experiment is that both the researchers and participants are

ignorant of the details of the hypothesis. It is meant to attempt to control the

researchers expectancy such as a researcher working for a pharmaceutical

company who is studying the efficacy of a new experimental drug that will lead to

a huge increase in sales if the drug works or money that is lost because it doesnt

result in a winning formula. A classical example of a double blind experiment, is


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the studying of a new product line of hamburgers where both the one eating the

hamburger and the researcher who is giving the hamburger are left unaware if in

fact the drug is the new product line or in fact a generic hamburger or a

competitors.

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