The data in the table below is 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 speeding up the process and eliminating
some non-value-added 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.
Use the date in table above and answer the following questions in the space provided below:
- 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 b1x, 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.)
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