MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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A) Use a two-tailed test with α = .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. 

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 research report. 

10. Recent research has shown that creative people are
more likely to cheat than their less-creative counter-
selec parts (Gino & Ariely, 2011). Participants in the study
first completed creativity assessment questionnaires
the po and then returned to the lab several days later for a
t on th 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
on the
to transfer their answers to a bubble sheet for computer
bisb
ance to scoring. However, the experimenter admitted that the
wrong bubble sheet had been copied so that the correct
For 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
olan paid based on the number of correct answers. Howev-
er, the researchers had secretly coded the original tests
bl and the bubble sheets so that they could measure the
degree of cheating for each participant. Assuming that
ted for
the participants were divided into two groups based on
b their creativity scores, the following data are similar to
the cheating scores obtained in the study.
As
sup o1 192olo igh-Creativity
Low-Creativity
r the t
(pc bo
Participants
Participants
a, the popled vari n = 27
ad olqmsa bapoo2nbns 00 =22.2ed olame2 ono
SS
n = 27
M = 7.41
M = 4.78
SS = 749.5 amse di SS = 830
2.86
= 22
%3D
%3D
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Transcribed Image Text:10. Recent research has shown that creative people are more likely to cheat than their less-creative counter- selec parts (Gino & Ariely, 2011). Participants in the study first completed creativity assessment questionnaires the po and then returned to the lab several days later for a t on th 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 on the to transfer their answers to a bubble sheet for computer bisb ance to scoring. However, the experimenter admitted that the wrong bubble sheet had been copied so that the correct For 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 olan paid based on the number of correct answers. Howev- er, the researchers had secretly coded the original tests bl and the bubble sheets so that they could measure the degree of cheating for each participant. Assuming that ted for the participants were divided into two groups based on b their creativity scores, the following data are similar to the cheating scores obtained in the study. As sup o1 192olo igh-Creativity Low-Creativity r the t (pc bo Participants Participants a, the popled vari n = 27 ad olqmsa bapoo2nbns 00 =22.2ed olame2 ono SS n = 27 M = 7.41 M = 4.78 SS = 749.5 amse di SS = 830 2.86 = 22 %3D %3D
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