Chipotle would like to know the degree to which punctuality at work is predictive of an employee’s monthly performance review. Chipotle randomly samples 6 employees, pulling the employment records for how often each employee has been late to work over the past month. Then, each employee’s boss provides an overall monthly review of that employee’s work, with the final review rating ranging from 1 (extremely poor performance at work) to 10 (exceptional performance at work). The data is as follows: Participant Number of Days Late Monthly Performance Review 1 2 8 2 7 7 3 0 9 4 1 5 5 6 3 6 9 5 For this problem, complete the following steps using simple linear regression by hand: Identify the two hypotheses. Determine the critical region for your decision (use α = 0.05). Compute the test statistic. Use the test statistic to make a decision and interpret that decision.
Chipotle would like to know the degree to which punctuality at work is predictive of an employee’s monthly performance review. Chipotle randomly samples 6 employees, pulling the employment records for how often each employee has been late to work over the past month. Then, each employee’s boss provides an overall monthly review of that employee’s work, with the final review rating ranging from 1 (extremely poor performance at work) to 10 (exceptional performance at work). The data is as follows:
Participant
Number of Days Late
Monthly Performance Review
1
2
8
2
7
7
3
0
9
4
1
5
5
6
3
6
9
5
For this problem, complete the following steps using simple linear regression by hand:
Identify the two hypotheses.
Determine the critical region for your decision (use α = 0.05).
Compute the test statistic.
Use the test statistic to make a decision and interpret that decision.
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