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b. Compute Cohen's d to measure the size of the effect. c. Write a sentence demonstrating how the results from the hypothesis test and the measure of effect size would appear in a rescarch report. 10. Recent research has shown that creative people are more likely to cheat than their less-creative counter- parts (Gino & 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 a bubble sheet 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. Howev- er, the researchers had secretly coded the original tests and the bubble sheets so that they could measure the கீபாoss 1- 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, W. High-Creativity Participants Low-Creativity Participants 27 M=4.78 27. 741 S. SS .05 to determine a. Use a one-tailed test with a= whether these data are sufficient to conclude that high-creativity people are more likely to cheat than people with lower levels of creativity.

b. Compute Cohen's d to measure the size of the effect. c. Write a sentence demonstrating how the results from the hypothesis test and the measure of effect size would appear in a rescarch report. 10. Recent research has shown that creative people are more likely to cheat than their less-creative counter- parts (Gino & 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 a bubble sheet 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. Howev- er, the researchers had secretly coded the original tests and the bubble sheets so that they could measure the கீபாoss 1- 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, W. High-Creativity Participants Low-Creativity Participants 27 M=4.78 27. 741 S. SS .05 to determine a. Use a one-tailed test with a= whether these data are sufficient to conclude that high-creativity people are more likely to cheat than people with lower levels of creativity.

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
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b. Compute Cohen's d to measure the size of the effect. c. Write a sentence demonstrating how the results from the hypothesis test and the measure of effect size would appear in a rescarch report.
Transcribed Image Text:b. Compute Cohen's d to measure the size of the effect. c. Write a sentence demonstrating how the results from the hypothesis test and the measure of effect size would appear in a rescarch report.
10. Recent research has shown that creative people are more likely to cheat than their less-creative counter- parts (Gino & 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 a bubble sheet 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. Howev- er, the researchers had secretly coded the original tests and the bubble sheets so that they could measure the கீபாoss 1- 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, W. High-Creativity Participants Low-Creativity Participants 27 M=4.78 27. 741 S. SS .05 to determine a. Use a one-tailed test with a= whether these data are sufficient to conclude that high-creativity people are more likely to cheat than people with lower levels of creativity.
Transcribed Image Text:10. Recent research has shown that creative people are more likely to cheat than their less-creative counter- parts (Gino & 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 a bubble sheet 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. Howev- er, the researchers had secretly coded the original tests and the bubble sheets so that they could measure the கீபாoss 1- 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, W. High-Creativity Participants Low-Creativity Participants 27 M=4.78 27. 741 S. SS .05 to determine a. Use a one-tailed test with a= whether these data are sufficient to conclude that high-creativity people are more likely to cheat than people with lower levels of creativity.
Expert Solution
Step 1

Let's denote the high creativity group by 1 and low creativity by 2. So the null and alternative hypothesis can be denoted as: H0:μ1=μ2 and Ha:μ1>μ2

First find the variance for both the groups and this will be equal to s2=SSn-1

s12=749.527-1=749.526=28.827s22=83027-1=83026=31.923

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