Reference no: EM131609143
Assignment
The main theme of Lecture is "How to evaluate process improvement after eliminating some non-value-added items". The table given in the homework shows the insurance claim approval time (days) from the first 12 weeks of the old process (from week 1 through week 12) where some non-value-added items are not removed. The table also shows the data of new process (the second 12 weeks; week 13 through week 24) after eliminating the non-value-added items. For the purpose of comparison, I changed the week number for the new process below.
Table: Insurance Claim Approval Times (days)
Old Process
|
|
|
New Process
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|
Week
|
Elapsed Time
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|
Week
|
Elapsed Time
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1
|
31.7
|
|
1
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24
|
2
|
27
|
|
2
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25.8
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3
|
33.8
|
|
3
|
31
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4
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30
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|
4
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23.5
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5
|
32.5
|
|
5
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28.5
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6
|
33.5
|
|
6
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25.6
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7
|
38.2
|
|
7
|
28.7
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8
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37.5
|
|
8
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27.4
|
9
|
29
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|
9
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28.5
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10
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31.3
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|
10
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25.2
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11
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38.6
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|
11
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24.5
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12
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39.3
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12
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23.5
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Please follow my instruction for each question of HW below.
1. Calculate the average elapsed time of each process and compare them.
2. The meaning of 29.32 in nothing, no practical interpretation. But the meaning of slope, 0.648 is very important. When you use this model for forecasting purpose, you can forecast the elapsed time (days) for week 13 and 14 as follows: week 13 means x = 13. Plug x value in the equation above, y = 29.32 + 0.648 (13) = 37.744 days week 14 means x = 14. Plug x value in the equation above, y = 29.32 + 0.648 (14) = 38.392 days. Please read and learn the relevant information about the regression model analysis from online.
Remember that this regression model is a very useful and mighty tool used by all scientists today. Spend time to study the basic of regression model. Thank you very much.
3. Based on your own judgment from two regression models you found, answer the question.
4. Simply compare the average numbers of two different process in question 1. I am not asking further to compare the slopes and interpret, which is a tough question for beginners.
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