Dan Ariely and colleagues have conducted some extremely interesting studies on c
ID: 3045786 • Letter: D
Question
Dan Ariely and colleagues have conducted some extremely interesting studies on cheating (see, for example Mazar, Amir, & Ariely, 2008). To provide an opportunity for cheating, participants are given a packet of problems and told they will be paid $0.50 for each correct answer. The experiment is setup, however, so that the participant doesn’t have to turn in their work, they simply have to state how many problems they solved to get paid. This provides a prime opportunity to cheat to earn extra money. In previous tests where the problems are properly scored, so no cheating, Ariely and colleagues found that scores are normally distributed: = 3.3, = 1.0. Here is a list of scores for participants who knew that their work would not be checked. Which of these would you suspect of cheating? Why? a. Participant 1: X = 4 b. Participant 2: X = 6 c. Participant 3: X = 7 d. Participant 4: X = 0
Dan Ariely and colleagues have conducted some extremely interesting studies on cheating (see, for example Mazar, Amir, & Ariely, 2008). To provide an opportunity for cheating, participants are given a packet of problems and told they will be paid $0.50 for each correct answer. The experiment is setup, however, so that the participant doesn’t have to turn in their work, they simply have to state how many problems they solved to get paid. This provides a prime opportunity to cheat to earn extra money. In previous tests where the problems are properly scored, so no cheating, Ariely and colleagues found that scores are normally distributed: = 3.3, = 1.0. Here is a list of scores for participants who knew that their work would not be checked. Which of these would you suspect of cheating? Why? a. Participant 1: X = 4 b. Participant 2: X = 6 c. Participant 3: X = 7 d. Participant 4: X = 0
Dan Ariely and colleagues have conducted some extremely interesting studies on cheating (see, for example Mazar, Amir, & Ariely, 2008). To provide an opportunity for cheating, participants are given a packet of problems and told they will be paid $0.50 for each correct answer. The experiment is setup, however, so that the participant doesn’t have to turn in their work, they simply have to state how many problems they solved to get paid. This provides a prime opportunity to cheat to earn extra money. In previous tests where the problems are properly scored, so no cheating, Ariely and colleagues found that scores are normally distributed: = 3.3, = 1.0. Here is a list of scores for participants who knew that their work would not be checked. Which of these would you suspect of cheating? Why? a. Participant 1: X = 4 b. Participant 2: X = 6 c. Participant 3: X = 7 d. Participant 4: X = 0
Dan Ariely and colleagues have conducted some extremely interesting studies on cheating (see, for example Mazar, Amir, & Ariely, 2008). To provide an opportunity for cheating, participants are given a packet of problems and told they will be paid $0.50 for each correct answer. The experiment is setup, however, so that the participant doesn’t have to turn in their work, they simply have to state how many problems they solved to get paid. This provides a prime opportunity to cheat to earn extra money. In previous tests where the problems are properly scored, so no cheating, Ariely and colleagues found that scores are normally distributed: = 3.3, = 1.0. Here is a list of scores for participants who knew that their work would not be checked. Which of these would you suspect of cheating? Why? a. Participant 1: X = 4 b. Participant 2: X = 6 c. Participant 3: X = 7 d. Participant 4: X = 0
Explanation / Answer
let us calculate Z for each participant where Z = (X- mean)/sogma
Z1 = 4-3.3 = 0.7
Z2 = 6-3.3 = 2.7
Z3 = 7-3.3 = 3.7
Z4 = 0-3.3 = -3.3
If we let the threshold of hypothesis testing to be 99%,
then Zthreshold = 2.33
This means Z2 and Z3 can be suspect of cheating
Related Questions
Navigate
Integrity-first tutoring: explanations and feedback only — we do not complete graded work. Learn more.