Insurance company data analysis

The data in the table are from a study conducted by an insurance company to determine the effect of changing
the process by which insurance claims are approved. The goal was to improve policyholder satisfaction by
expediting the process and eliminating some extraneous approval steps in the process. The response
measured was the average time required to approve and mail all claims initiated in a week. The new procedure
was tested for 12 weeks, and the results were compared to the process performance for the 12 weeks prior to
instituting the change.
Table: Insurance Claim Approval Times (Days)
Old Process Elapsed Time New Process Elapsed Time
Week Week
1 31.7 13 24
2 27 14 25.8
3 33.8 15 31
4 30 16 23.5
5 32.5 17 28.5
6 33.5 18 25.6
7 38.2 19 28.7
8 37.5 20 27.4
9 29 21 28.5
10 31.5 22 25.2
11 38.6 23 24.5
12 39.3 24 23.5
Use the data in the table and submit the answers to the following questions in a Word document:
What was the average effect of the process change? Did the process average increase or decrease, and by
how much?
Analyze the data using the regression model y= b0 + b1 x, where y = time to approve and mail a claim (weekly
average), x = 0 for the old process, and x = 1 for the new process.
How does this model measure the effect of the process change?
How much did the process performance change on the average? (Hint: Compare the values of b1 and the
average of new process performance minus the average of the performance of the old process.)