?A sample of n = 9 individuals participates in a repeated-measures study that produces a

Research indicates that the color red increases men’s attraction to women (Elliot and Niesta, 2008). In the original study, men were shown women’s photographs presented on either a white or a red background. Photographs presented on red were rated significantly more attractive than the same photographs mounted on white. In a similar study, a researcher prepares a set of 30 women’s photographs, with 15 mounted on a white background and 15 mounted on red. One picture is identified as the test photograph, and appears twice in the set, once on white and once on red. Each male participant looks through the entire set of photographs and rates the attractiveness of each woman on a 10-point scale. The following table summarizes the ratings of the test photograph for a sample of n = 9 men. Are the ratings for the test photograph significantly different when it is presented on a red background compared to a white background? Use a two-tailed test with \(\alpha = .01\). Text Transcription: alpha=.01

Example 11.2 in this chapter presented a repeated measures research study demonstrating that swearing can help reduce ratings of pain (Stephens, Atkins, & Kingston, 2009). In the study, each participant was asked to plunge a hand into icy water and keep it there as long as the pain would allow. In one condition, the participants repeated their favorite curse words while their hands were in the water. In the other condition, the participants repeated a neutral word. In addition to lowering the participants’ perception of pain, swearing also increased the amount of time that they were able to tolerate the pain. Data similar to the results obtained in the study are shown in the following table. (a) Do these data indicate a significant difference in pain tolerance between the two conditions? Use a two-tailed test with \(\alpha = .05\). (b) Compute \(r^{2}\) , the percentage of variance accounted for, to measure the size of the treatment effect. (c) Write a sentence demonstrating how the results of the hypothesis test and the measure of effect size would appear in a research report. Text Transcription: alpha=.05 r^2

(a) A repeated-measures study with a sample of n = 16 participants produces a mean difference of \(M_{D} = 3\) with a standard deviation of s = 4. Use a two-tailed hypothesis test with \(\alpha = .05\) to determine whether this sample provides evidence of a significant treatment effect. (b) Now assume that the sample standard deviation is s = 12 and repeat the hypothesis test. (c) Explain how the size of the sample standard deviation influences the likelihood of finding a significant mean difference. Text Transcription: M_D=3 alpha=.05

(a) A repeated-measures study with a sample of n = 16 participants produces a mean difference of \(M_{D} = 4\) with a standard deviation of s = 8. Use a two-tailed hypothesis test with \(\alpha = .05\) to determine whether it is likely that this sample came from a population with \(\mu_{D} = 0\). (b) Now assume that the sample mean difference is \(M_{D} = 10\), and once again visualize the sample distribution. Use a two-tailed hypothesis test with \(\alpha = .05\) to determine whether it is likely that this sample came from a population with \(\mu_{D} = 0\). (c) Explain how the size of the sample mean difference influences the likelihood of finding a significant mean difference. Text Transcription: M_D=4 alpha=.05 mu_D=0 M_D=10

A sample of difference scores from a repeated measures experiment has a mean of \(M_{D} = 3\) with a standard deviation of s = 4. (a) If n = 4, is this sample sufficient to reject the null hypothesis using a two-tailed test with \(\alpha = .05\)? (b) Would you reject \(H_{0}\) if n = 16? Again, assume a two-tailed test with \(\alpha = .05\). (c) Explain how the size of the sample influences the likelihood of finding a significant mean difference. Text Transcription: M_D=3 alpha=.05 H_0

Participants enter a research study with unique characteristics that produce different scores from one person to another. For an independent-measures study, these individual differences can cause problems. Identify the problems and briefly explain how they are eliminated or reduced with a repeated-measures study.

In the Chapter Preview we described a study showing that students had more academic problems following nights with less than average sleep compared to nights with more than average sleep (Gillen-O’Neel, Huynh, & Fuligni, 2013). Suppose a researcher is attempting to replicate this study using a sample of n = 8 college freshmen. Each student records the amount of study time and amount of sleep each night and reports the number of academic problems each day. The following data show the results from the study. (a) Treat the data as if the scores are from an independent-measures study using two separate samples, each with n = 8 participants. Compute the pooled variance, the estimated standard error for the mean difference, and the independent-measures t statistic. Using a two-tailed test with \(\alpha = .05\), is there a significant difference between the two sets of scores? (b) Now assume that the data are from a repeated measures study using the same sample of n = 8 participants in both treatment conditions. Compute the variance for the sample of difference scores, the estimated standard error for the mean difference and the repeated-measures t statistic. Using a two-tailed test with \(\alpha = .05\), is there a significant difference between the two sets of scores? (You should find that the repeated-measures design substantially reduces the variance and increases the likelihood of rejecting \(H_{0}\).) Text Transcription: alpha=.05 H_0

The previous problem demonstrates that removing individual differences can substantially reduce variance and lower the standard error. However, this benefit only occurs if the individual differences are consistent across treatment conditions. In problem 21, for example, the participants with the highest scores in the more-sleep condition also had the highest scores in the less-sleep condition. Similarly, participants with the lowest scores in the first condition also had the lowest scores in the second condition. To construct the following data, we started with the scores in problem 21 and scrambled the scores in treatment 1 to eliminate the consistency of the individual differences. (a) Treat the data as if the scores are from an independent-measures study using two separate samples, each with n = 8 participants. Compute the pooled variance, the estimated standard error for the mean difference, and the independent-measures t statistic. Using a two-tailed test with \(\alpha = .05\), is there a significant difference between the two sets of scores? Note: The scores in each treatment are the same as in Problem 21. Nothing has changed. (b) Now assume that the data are from a repeated measures study using the same sample of n = 8 participants in both treatment conditions. Compute the variance for the sample of difference scores, the estimated standard error for the mean difference and the repeated-measures t statistic. Using a two-tailed test with \(\alpha = .05\), is there a significant difference between the two sets of scores? (You should find that removing the individual differences with a repeated-measures t no longer reduces the variance because there are no consistent individual differences.) Text Transcription: alpha=.05

For the each of the following studies determine whether a repeated-measures t test is the appropriate analysis. Explain your answers. (a) A researcher is examining the effect of violent video games on behavior by comparing aggressive behaviors for one group who just finished playing a violent game with another group who played a neutral game. (b) A researcher is examining the effect on humor on memory by presenting a group of participants with a series of humorous and not humorous sentences and them recording how many of each type of sentence is recalled by each participant. (c) A researcher is evaluating the effectiveness of a new cholesterol medication by recording the cholesterol level for each individual in a sample before they start taking the medication and again after 8 weeks with the medication.

What is the defining characteristic of a repeatedmeasures or within-subjects research design?

Explain the difference between a matched-subjects design and a repeated-measures design.

A researcher conducts an experiment comparing two treatment conditions with 20 scores in each treatment condition. (a) If an independent-measures design is used, how many subjects are needed for the experiment? (b) If a repeated-measures design is used, how many subjects are needed for the experiment? (c) If a matched-subjects design is used, how many subjects are needed for the experiment?

A sample of n = 9 individuals participates in a repeated-measures study that produces a sample mean difference of \(M_{D} = 4.25\) with SS = 128 for the difference scores. (a) Calculate the standard deviation for the sample of difference scores. Briefly explain what is measured by the standard deviation. (b) Calculate the estimated standard error for the sample mean difference. Briefly explain what is measured by the estimated standard error. Text Transcription: M_D=4.25

In the Preview for Chapter 2, we presented a study showing that a woman shown in a photograph was judged as less attractive when the photograph showed a visible tattoo compared to the same photograph with the tattoo removed (Resenhoeft, Villa, & Wiseman, 2008). Suppose a similar experiment is conducted as a repeated-measures study. A sample of n = 12 males looks at a set of 30 photographs of women and rates the attractiveness of each woman using a 5-point scale (5 = most positive). One photograph appears twice in the set, once with a tattoo and once with the tattoo removed. For each participant, the researcher records the difference between the two ratings of the same photograph. On average, the photograph without the tattoo is rated \(M_{D} = 1.2\) points higher than the photograph with the tattoo, with SS = 33 for the difference scores. Does the presence of a visible tattoo have a significant effect on the attractiveness ratings? Use a two-tailed test with \(\alpha = .05\) Text Transcription: M_D=1.2 alpha=.05.

The following data are from a repeated-measures study examining the effect of a treatment by measuring a group of n = 6 participants before and after they receive the treatment. (a) Calculate the difference scores and \(M_{D}\). (b) Compute SS, sample variance, and estimated standard error. (c) Is there a significant treatment effect? Use \(\alpha = .05\), two tails. Text Transcription: M_D alpha=.05

When you get a surprisingly low price on a product do you assume that you got a really good deal or that you bought a low-quality product? Research indicates that you are more likely to associate low price and low quality if someone else makes the purchase rather than yourself (Yan and Sengupta, 2011). In a similar study, n = 16 participants were asked to rate the quality of low-priced items under two scenarios: purchased by a friend or purchased yourself. The results produced a mean difference of \(M_{D} = 2.6\) and SS = 135, with self-purchases rated higher. (a) Is the judged quality of objects significantly different for self-purchases than for purchases made by others? Use a two-tailed test with \(\alpha = .05\). (b) Compute Cohen’s d to measure the size of the treatment effect. Text Transcription: M_D=2.6 alpha=.05

Masculine-themed words (such as competitive, independent, analyze, strong) are commonly used in job recruitment materials, especially for job advertisements in male-dominated areas (Gaucher, Friesen, & Kay, 2010). The same study found that these words also make the jobs less appealing to women. In a similar study, female participants were asked to read a series of job advertisements and then rate how interesting or appealing the job appeared to be. Half of the advertisements were constructed to include several masculine-themed words and the others were worded neutrally. The average rating for each type of advertisement was obtained for each participant. For n = 25 participants, the mean difference between the two types of advertisements is \(M_{D} = 1.32\) points (neutral ads rated higher) with SS = 150 for the difference scores. (a) Is this result sufficient to conclude that there is a significant difference in the ratings for two types of advertisements? Use a two-tailed test with \(\alpha = .05\). (b) Compute \(r^{2}\) to measure the size of the treatment effect. (c) Write a sentence describing the outcome of the hypothesis test and the measure of effect size as it would appear in a research report. Text Transcription: M_D=1.32 alpha=.05 r^2

. The stimulant Ritalin has been shown to increase attention span and improve academic performance in children with ADHD (Evans et al., 2001). To demonstrate the effectiveness of the drug, a researcher selects a sample of n = 20 children diagnosed with the disorder and measures each child’s attention span before and after taking the drug. The data show an average increase of attention span of \(M_{D} = 4.8\) minutes with a variance of \(s^{2} = 125\) for the sample of difference scores. (a) Is this result sufficient to conclude that Ritalin significantly improves attention span? Use a one tailed test with \(\alpha = .05\). (b) Compute the 80% confidence interval for the mean change in attention span for the population. Text Transcription: M_D=4.8 s^2=125 alpha=.05

College athletes, especially males, are often perceived as having very little interest in the academic side of their college experience. One common problem is class attendance. To address the problem of class attendance, a group of researchers developed and demonstrated a relatively simple but effective intervention (Bicard, Lott, Mills, Bicard, & Baylot-Casey, 2012). The researchers asked each athlete to text his academic counselor “in class” as soon as he arrived at the classroom. The researchers found significantly better attendance after the students began texting. In a similar study, a researcher monitored class attendance for a sample of n = 16 male athletes during the first 3 weeks of the semester and recorded the number of minutes that each student was late to class. The athletes were then asked to begin texting their arrival at the classroom and the researcher continued to monitor attendance for another 3 weeks. For each athlete, the average lateness for the first three weeks and for the second three weeks were calculated, and the difference score was recorded. The data showed that lateness to class decreased by an average of \(M_{D} = 21\) minutes with SS = 2940 when the students were texting. (a) Use a two-tailed test with \(\alpha = .01\) to determine whether texting produced a significant change in attendance. (b) Compute a 95% confidence interval to estimate the mean change in attendance for the population. Text Transcription: M_D=21 alpha=.01

Callahan (2009) demonstrated that Tai Chi can significantly reduce symptoms for individuals with arthritis. Participants were 18 years old or older with doctordiagnosed arthritis. Self-reports of pain and stiffness were measured at the beginning of an 8-week Tai Chi course and again at the end. Suppose that the data produced an average decrease in pain and stiffness of \(M_{D} = 8.5\) points with a standard deviation of 21.5 for a sample of n = 40 participants. (a) Use a two-tailed test with \(\alpha = .05\) to determine whether the Tai Chi had a significant effect on pain and stiffness. (b) Compute Cohen’s d to measure the size of the treatment effect. Text Transcription: M_D=8.5 alpha=.05

Research results indicate that physically attractive people are also perceived as being more intelligent (Eagly, Ashmore, Makhijani, & Longo, 1991). As a demonstration of this phenomenon, a researcher obtained a set of 10 photographs, 5 showing men who were judged to be attractive and 5 showing men who were judged to be unattractive. The photographs were shown to a sample of n = 25 college students and the students were asked to rate the intelligence of the person in the photo on a scale from 1 to 10. For each student, the researcher determined the average rating for the 5 attractive photos and the average for the 5 unattractive photos, and then computed the difference between the two scores. For the entire sample, the average difference was \(M_{D} = 2.7\) (attractive photos rated higher) with s = 2.00. Are the data sufficient to conclude that there was a significant difference in perceived intelligence for the two sets of photos? Use a two-tailed test with \(\alpha = .05\). Text Transcription: M_D=2.7 alpha=.05

There is some evidence suggesting that you are likely to improve your test score if you rethink and change answers on a multiple-choice exam (Johnston, 1975). To examine this phenomenon, a teacher gave the same final exam to two sections of a psychology course. The students in one section were told to turn in their exams immediately after finishing, without changing any of their answers. In the other section, students were encouraged to reconsider each question and to change answers whenever they felt it was appropriate. Before the final exam, the teacher had matched 9 students in the first section with 9 students in the second section based on their midterm grades. For example, a student in the no-change section with an 89 on the midterm exam was matched with student in the change section who also had an 89 on the midterm. The difference between the two final exam grades for each matched pair was computed and the data showed that the students who were allowed to change answers scoring higher by an average of \(M_{D} = 7\) points with SS = 288. (a) Do the data indicate a significant difference between the two conditions? Use a two-tailed test with \(\alpha = .05\). (b) Construct a 95% confidence interval to estimate the size of the population mean difference. (c) Write a sentence demonstrating how the results of the hypothesis test and the confidence interval would appear in a research report. Text Transcription: M_D=7 alpha=.05