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Recent research has shown that creative people are more likely to cheat than their less creative counterparts (Gino and Ariely, 2011). Participants in the study first completed creativity assessment questionnaires and then returned to the lab several days later for a series of tasks. One task was a multiple-choice general knowledge test for which the participants circled their answers on the test sheet. Afterward, they were asked to transfer their answers to bubble sheets for computer scoring. However, the experimenter admitted that the wrong bubble sheet had been copied so that the correct answers were still faintly visible. Thus, the participants had an opportunity to cheat and inflate their test scores. Higher scores were valuable because participants were paid based on the number of correct answers. However, the researchers had secretly coded the original tests and the bubble sheets so that they could measure the degree of cheating for each participant. Assuming that the participants were divided into two groups based on their creativity scores, the following data are similar to the cheating scores obtained in the study. High-Creativity Participants Low-Creativity Participants n - 27 n - 27 M = 7.41 M - 4.78 SS - 749,5 SS = 830 Use a one-tailed test with a = .05 to determine whether these data are sufficient to conclude that high-creativity people are more likely to cheat than people with lower levels of creativity. Pooled Variance Estimated Standard Error t Statistic Critical Values

Recent research has shown that creative people are more likely to cheat than their less creative counterparts (Gino and Ariely, 2011). Participants in the study first completed creativity assessment questionnaires and then returned to the lab several days later for a series of tasks. One task was a multiple-choice general knowledge test for which the participants circled their answers on the test sheet. Afterward, they were asked to transfer their answers to bubble sheets for computer scoring. However, the experimenter admitted that the wrong bubble sheet had been copied so that the correct answers were still faintly visible. Thus, the participants had an opportunity to cheat and inflate their test scores. Higher scores were valuable because participants were paid based on the number of correct answers. However, the researchers had secretly coded the original tests and the bubble sheets so that they could measure the degree of cheating for each participant. Assuming that the participants were divided into two groups based on their creativity scores, the following data are similar to the cheating scores obtained in the study. High-Creativity Participants Low-Creativity Participants n - 27 n - 27 M = 7.41 M - 4.78 SS - 749,5 SS = 830 Use a one-tailed test with a = .05 to determine whether these data are sufficient to conclude that high-creativity people are more likely to cheat than people with lower levels of creativity. Pooled Variance Estimated Standard Error t Statistic Critical Values

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Do: Chapter 10 End-of-Chapter Problems O Reject Ho. Higher creativity people are not significantly more likely to cheat. O Fail to reject Ho. Higher creativity people are not significantly more likely to cheat. O Fail to reject Ho. Higher creativity people are significantly more likely to cheat. O Reject Ho. Higher creativity people are significantly more likely to cheat. Compute Cohen's d to measure the size of the effect. O 0.09 O 0.06 O 0.48 O 1.75 Write a sentence demonstrating how the results from the hypothesis test and the measure of effect size would appear in a research report. The results show that higher-creativity people significantly more likely to cheat than people who reflect lower creativity,
Transcribed Image Text:Do: Chapter 10 End-of-Chapter Problems O Reject Ho. Higher creativity people are not significantly more likely to cheat. O Fail to reject Ho. Higher creativity people are not significantly more likely to cheat. O Fail to reject Ho. Higher creativity people are significantly more likely to cheat. O Reject Ho. Higher creativity people are significantly more likely to cheat. Compute Cohen's d to measure the size of the effect. O 0.09 O 0.06 O 0.48 O 1.75 Write a sentence demonstrating how the results from the hypothesis test and the measure of effect size would appear in a research report. The results show that higher-creativity people significantly more likely to cheat than people who reflect lower creativity,
Do: Chapter 10 End-of-Chapter Problems Recent research has shown that creative people are more likely to cheat than their less creative counterparts (Gino and Ariely, 2011). Participants in the study first completed creativity assessment questionnaires and then returned to the lab several days later for a series of tasks. One task was a multiple-choice general knowledge test for which the participants circled their answers on the test sheet. Afterward, they were asked to transfer their answers to bubble sheets for computer scoring. However, the experimenter admitted that the wrong bubble sheet had been copied so that the correct answers were still faintly visible. Thus, the participants had an opportunity to cheat and inflate their test scores. Higher scores were valuable because participants were paid based on the number of correct answers. However, the researchers had secretly coded the original tests and the bubble sheets so that they could measure the degree of cheating for each participant. Assuming that the participants were divided into two groups based on their creativity scores, the following data are similar to the cheating scores obtained in the study. High-Creativity Participants Low-Creativity Participants n = 27 n = 27 M = 7.41 M = 4.78 SS = 749.5 SS = 830 Use a one-tailed test with a = .05 to determine whether these data are sufficient to conclude that high-creativity people are more likely to cheat than people with lower levels of creativity. Pooled Variance Estimated Standard Error t Statistic Critical Values
Transcribed Image Text:Do: Chapter 10 End-of-Chapter Problems Recent research has shown that creative people are more likely to cheat than their less creative counterparts (Gino and Ariely, 2011). Participants in the study first completed creativity assessment questionnaires and then returned to the lab several days later for a series of tasks. One task was a multiple-choice general knowledge test for which the participants circled their answers on the test sheet. Afterward, they were asked to transfer their answers to bubble sheets for computer scoring. However, the experimenter admitted that the wrong bubble sheet had been copied so that the correct answers were still faintly visible. Thus, the participants had an opportunity to cheat and inflate their test scores. Higher scores were valuable because participants were paid based on the number of correct answers. However, the researchers had secretly coded the original tests and the bubble sheets so that they could measure the degree of cheating for each participant. Assuming that the participants were divided into two groups based on their creativity scores, the following data are similar to the cheating scores obtained in the study. High-Creativity Participants Low-Creativity Participants n = 27 n = 27 M = 7.41 M = 4.78 SS = 749.5 SS = 830 Use a one-tailed test with a = .05 to determine whether these data are sufficient to conclude that high-creativity people are more likely to cheat than people with lower levels of creativity. Pooled Variance Estimated Standard Error t Statistic Critical Values
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