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Response bias arises in a variety of ways The respondent may not give truthful responses to a question (perhaps she or he is ashamed of the truth); the respondent may fail to understand the question (you ask if a person is educated but fail to distinguish between levels of education); the respondent desires to please the interviewer (questions concerning race relations may well solicit different answers depending on the race of the interviewer); the ordering of the question may influence the response ( Do you prefer A to B may get different responses than Do you prefer B to A ) example: What form of bias do you suspect in the following situation You are a school principal and want to know students level of satisfaction with the counseling services at your school You direct one of the school counselors to ask her next 25 counselees how favorably they view the counseling services at the school solution: A number of things would be wrong with the data you get from such a survey First, the sample is nonrandom it is a sample of convenience obtained by selecting 25 consecutive counselees They may or may not be representative of students who use counseling service You don t know Second, you are asking people who are seeing their counselor about their opinion of counseling You will probably get a more favorable view of the counseling services than you would if you surveyed the general population of the school (would students really unhappy with the counseling services voluntarily be seeing their counselor ) Also, because the counselor is administering the
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126 U Step 4 Review the Knowledge You Need to Score High
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questionnaire, the respondents would have a tendency to want to please the interviewer The sample certainly suffers from undercoverage only a small subset of the general population is actually being interviewed What do those not being interviewed think of the counseling
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Experiments and Observational Studies
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Statistical Significance
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One of the desirable outcomes of a study is to help us determine cause and effect We do this by looking for differences between groups that are so great that we cannot reasonably attribute the difference to chance We say that a difference between what we would expect to find if there were no treatment and what we actually found is statistically significant if the difference is too great to attribute to chance We discuss numerical methods of determining significance in s 11 15 An experiment is a study in which the researcher imposes some sort of treatment on the experimental units (which can be human usually called subjects in that case) In an experiment, the idea is to determine the extent to which treatments (the explanatory variable(s)) affects outcomes (the response variable (s)) For example, a researcher might vary the rewards to different work group members to see how that affects the group s ability to perform a particular task An observational study, on the other hand, simply observes and records behavior but does not attempt to impose a treatment in order to manipulate the response
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Exam Tip: The distinction between an experiment and an observational study is an important one There is a reasonable chance that you will be asked to show you understand this distinction on the exam Be sure this section makes sense to you example: A group of 60 exercisers are classified as walkers or runners A longitudinal study (one conducted over time) is conducted to see if there are differences between the groups in terms of their scores on a wellness index This is an observational study because, although the two groups differ in an important respect, the researcher is not manipulating any treatment Walkers and runners are simply observed and measured Note that the groups in this study are self-selected That is, they were already in their groups before the study began The researchers just noted their group membership and proceeded to make observations There may be significant differences between the groups in addition to the variable under study example: A group of 60 volunteers who do not exercise are randomly assigned to one of the two fitness programs One group of 30 is enrolled in a daily walking program, and the other group is put into a running program After a period of time, the two groups are compared based on their scores on a wellness index This is an experiment because the researcher has imposed the treatment (walking or running) and then measured the effects of the treatment on a defined response It may be, even in a controlled experiment, that the measured response is a function of variables present in addition to the treatment variable A confounding variable is one that has an effect on the outcomes of the study but whose effects cannot be separated from those of the treatment variable A lurking variable is one that has an effect on the outcomes of
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