An investment idea: 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. 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
1 32 13 30
2 30 14 24.6
3 35.8 15 33
4 36 16 20
5 30.5 17 23.5
6 34.5 18 22.6
7 39.5 19 27.4
8 38.5 20 22.7
9 39 21 25.5
10 41.5 22 23.2
11 39.6 23 21.5
12 40.3 24 20.5
Use the data in the table and submit the answers to the following questions in a Word document:
In Excel, calculate the average effect of each process. Did the process change? Did the process average increase or decrease, and by how much? Copy-paste your Excel calculations into your Word Document.
In Excel, create the Linear Regression Model.
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. Copy-paste the Regression Model into your Word Document.
How does this model measure the effect of the process change?
How much did the process performance change on average?
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