6. Visualizing variability A researcher designs an intervention to combat anti-Arab oppression.
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Visualizing variability researcher designs an intervention to combat anti-Semitism He also designs questionnaire to measure anti-Semitism so he can test the participants' level of anti-Semitism before and after the intervention. He tests one version of his questionnaire with 45 statements and shorter version with 12 statements In both questionnaires the participants respond to each statement with rating on 5-point Likert scale with equaling strongly disagree and equaling strongly agree_ The overall score for each participant is the mean of his or her ratings for the different statements on the questionnaire Look at the following graphs_ Graph graphs the results from the short version, and Graph II graphs the results from the long version_ Graph Graph II PARTICIPANTS PARTICIPANTS SHORT QUESTIONNAIRE SCORE LONG QUESTIONNAIRE SCORE Complete the following sentences by trusting your eyes to see meaningful differences in the two graphs_ The range for Graph the range for Graph II, The mean for Graph the mean for Graph II. The variance for Graph the variance for Graph II_ This implies that the shorter questionnaire will be before and after the intervention_ than the longer questionnaire at detecting differences
Suman K.
The captain of each precinct of a metropolitan police department selected two officers to participate in a program designed to reduce prejudice by increasing sensitivity to racial and ethnic group differences and community issues. The training program took place every Friday morning for 3 months. At the first and last meetings, the officers completed a measure of prejudice. To assess the effectiveness of the program, the average prejudice score at the first meeting was compared with the average score at the last meeting. It was found that the average score was in fact lower following the training program. What type of design is this? What specific problems arise if you try to conclude that the training program was responsible for the reduction in prejudice?
Adi S.
An area of research in biomechanics and gerontology concerns falls and fall-related injuries, especially for elderly people. Recent studies have focused on how individuals respond to large postural disturbances (e.g., tripping, induced slips). One question is whether subjects can be instructed to improve their recovery from such disturbances. Suppose researchers want to compare two such recovery strategies, lowering (quickly stepping down with front leg and then raising back leg over the object) and elevating (lifting front leg over the object). Subjects will have first been trained on one of these two recovery strategies, and they will be asked to apply it after they feel themselves tripping. The researchers will then induce the subject to trip while walking (but harnessed for safety) using a concealed mechanical obstacle. Suppose the following 24 subjects have agreed to participate in such a study: Females: Alisha, Alice, Betty, Martha, Audrey, Mary, Barbie, Anna Males: Matt, Peter, Shawn, Brad, Michael, Kyle, Russ, Patrick, Bob, Kevin, Mitch, Marvin, Paul, Pedro, Roger, Sam 1a. One way to design this study would be to assign the 8 females to use the elevating strategy and the 16 males to use the lowering strategy. Would this be a reasonable strategy? Why not? 1b. One way to deal with this issue is to assign 4 females and 8 males to each group. Show how the proportion of males in each group is the same. 1c. Now, if you saw a difference in the proportion of trips in the two groups, could it be because of the sex of the subject? Why or why not? Could it be due to other variables, distinct from the recovery strategy? Why or why not? 1d. Because there will always be more potential confounding variables which could be distributed unevenly between the groups being compared, identify a better method for deciding who uses which strategy. 1e. Let's explore the process of random assignment to determine whether it does "work." First, let's focus on the sex (male vs. female) variable. Suppose we put each person's name on a slip, put those slips in a hat and mix them up thoroughly, and then randomly draw out 12 slips for names of people to assign to the elevating strategy. What proportion of this group do you expect will be male? What proportion of the lowering strategy do you expect will be male? Do you think we will always get an 8/8 split (8 males in each treatment group)? 1f. To repeat this random assignment a large number of times to observe the long-run behavior, we will use the Randomizing Subjects applet. Open the applet and press the Randomize button. What proportion of subjects assigned to Group 1 are men? Of Group 2? What is the difference in these two proportions? 1g. Press the Randomize button again. Was the difference in proportions of men the same this time? 1h. Change the number of replications from 1 to 198 (for 200 total), uncheck the Animate option, and press the Randomize button. The dotplot will display the difference between the two proportions of men for each of the 200 repetitions of the random assignment process. Where are these values centered? 1i. Does random assignment always equally distribute/balance the men and women between the two groups? Is there a tendency for there to be a similar proportion of men in the two groups? Explain. 1j. Prior research has also shown that the likelihood of falling is related to variables such as walking speed, stride rate, and height, so we would like the random assignment to distribute these variables equally between the groups as well. In the applet, use the pull-down menu to switch from the sex-of-participant variable to the height variable. The dotplot now displays the differences in average height between Group 1 and Group 2 for these 200 repetitions. In the long run, does random assignment tend to equally distribute the height variable between the two groups? Explain how you are deciding. 1k. Suppose there is a "balance gene" that is related to people's ability to recover from a trip. We didn't know about this gene ahead of time, but if you select the Reveal gene? button and then select gene from the pull-down menu, the applet shows you this gene information for each subject and also how the proportions with the gene differ in the two groups. Does this variable tend to equalize between the two groups in the long run? Explain. 1l. Suppose there were other "x-variables" that we could not measure such as stride rate or walking speed. Select the Reveal both? button and use the pull-down menu to display the results for the x-variable (X-var). Does random assignment generally succeed in equalizing this variable between the two groups or is there a tendency for one group to always have higher results for the x-variable? Explain. 1m. Suppose this study finds a statistically significant difference between the two groups. What conclusion would you draw? For what population? What additional information would you need to know? 1n. As in #1m, if you obtain a statistically significant result, what does that suggest about the potential for a cause-and-effect relationship? Why?
Patha S.
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