In: Statistics and Probability
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.
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 date in the table above and answer the following questions in the space provided below:
(a) The mean elapsed time is found for old process is 33.55 and for new process is 26.35 and the difference in mean are found statistically significant as pvalue is less than 0.05 i.e. 0.000 in table1. The elapsed time is decreasing by the new process and the difference is 7.15
(b) The regreaaion equation is found to predict the elapsed time for old and new process is
Elapsed time = 33.55 - 7.2 * type of process
If the process is new then type of process = 1 otherwise 0
The effect of the process is significantly impact on the elapsed time as the pvalue is less than 0.05 i.e. 0.000
The process performance change on the average is - 7.2 which is the difference in mean of old and new process elapsed time.