Levi-Strauss Co manufactures clothing. The quality control department measures weekly values of different suppliers for the percentage difference of waste between the layout on the computer and the actual waste when the clothing is made (called run-up). The data is in the following table, and there are some negative values because sometimes the supplier is able to layout the pattern better than the computer ("Waste run up," 2013). Table #11.3.3: Run-ups for Different Plants Making Levi Strauss Clothing Plant 1 Plant 2 Plant 3 Plant 4 Plant 5 1.2 16.4 12.1 11.5 24 10.1 -6 9.7 10.2 -3.7 -2 -11.6 7.4 3.8 8.2 1.5 -1.3 -2.1 8.3 9.2 -3 4 10.1 6.6 -9.3 -0.7 17 4.7 10.2 8 3.2 3.8 4.6 8.8 15.8 2.7 4.3 3.9 2.7 22.3 -3.2 10.4 3.6 5.1 3.1 -1.7 4.2 9.6 11.2 16.8 2.4 8.5 9.8 5.9 11.3 0.3 6.3 6.5 13 12.3 3.5 9 5.7 6.8 16.9 -0.8 7.1 5.1 14.5 19.4 4.3 3.4 5.2 2.8 19.7 -0.8 7.3 13 3 -3.9 7.1 42.7 7.6 0.9 3.4 1.4 70.2 1.5 0.7 3 8.5 2.4 6 1.3 2.9 Do the data show that there is a difference between some of the suppliers? Test at the 1% level ********************************************************************** Let x1 = percentage difference of waste between the layout on the computer and the actual waste when the clothing is made (called run-up) from plant 1 Let x2 = percentage difference of waste between the layout on the computer and the actual waste of run-up from plant 2 Let x3 = percentage difference of waste between the layout on the computer and the actual waste of run-up from plant 3 Let x4 = percentage difference of waste between the layout on the computer and the actual waste of run-up from plant 4 Let x5 = percentage difference of waste between the layout on the computer and the actual waste of run-up from plant 5 Let μ1 = mean percentage difference of waste between the layout on the computer and the actual waste of run-up from plant 1 Let μ2 = mean percentage difference of waste between the layout on the computer and the actual waste of run-up from plant 2 Let μ3 = mean percentage difference of waste between the layout on the computer and the actual waste of run-up from plant 3 Let μ4 = mean percentage difference of waste between the layout on the computer and the actual waste of run-up from plant 4 Let μ5 = mean percentage difference of waste between the layout on the computer and the actual waste of run-up from plant 5 (vii) Calculate sample mean and sample standard deviation for Plant 4 sample Enter sample mean in decimal form to nearest hundredth, then comma, then sample standard deviation in decimal form to nearest hundredth. Examples of correctly entered answers: 13.27,2.31 0.27,0.06 -10.30,0.79 (viii) Calculate sample mean and sample standard deviation for Plant 5 sample Enter sample mean in decimal form to nearest hundredth, then comma, then sample standard deviation in decimal form to nearest hundredth. Examples of correctly entered answers: 13.27,2.31 0.27,0.06 -10.30,0.79 (ix) Using technology, determine F ratio test statistic and corresponding p-value. Enter test statistic to nearest hundredth, then enter comma, then enter p-value to nearest thousandth. Examples of correctly entered responses: 12.33,0.004 7.50,0.000 6.77,0.504
Q9C
Levi-Strauss Co manufactures clothing. The quality control department measures weekly values of different suppliers for the percentage difference of waste between the layout on the computer and the actual waste when the clothing is made (called run-up). The data is in the following table, and there are some negative values because sometimes the supplier is able to layout the pattern better than the computer ("Waste run up," 2013).
Table #11.3.3: Run-ups for Different Plants Making Levi Strauss Clothing
|
Plant 1 |
Plant 2 |
Plant 3 |
Plant 4 |
Plant 5 |
|
1.2 |
16.4 |
12.1 |
11.5 |
24 |
|
10.1 |
-6 |
9.7 |
10.2 |
-3.7 |
|
-2 |
-11.6 |
7.4 |
3.8 |
8.2 |
|
1.5 |
-1.3 |
-2.1 |
8.3 |
9.2 |
|
-3 |
4 |
10.1 |
6.6 |
-9.3 |
|
-0.7 |
17 |
4.7 |
10.2 |
8 |
|
3.2 |
3.8 |
4.6 |
8.8 |
15.8 |
|
2.7 |
4.3 |
3.9 |
2.7 |
22.3 |
|
-3.2 |
10.4 |
3.6 |
5.1 |
3.1 |
|
-1.7 |
4.2 |
9.6 |
11.2 |
16.8 |
|
2.4 |
8.5 |
9.8 |
5.9 |
11.3 |
|
0.3 |
6.3 |
6.5 |
13 |
12.3 |
|
3.5 |
9 |
5.7 |
6.8 |
16.9 |
|
-0.8 |
7.1 |
5.1 |
14.5 |
|
|
19.4 |
4.3 |
3.4 |
5.2 |
|
|
2.8 |
19.7 |
-0.8 |
7.3 |
|
|
13 |
3 |
-3.9 |
7.1 |
|
|
42.7 |
7.6 |
0.9 |
3.4 |
|
|
1.4 |
70.2 |
1.5 |
0.7 |
|
|
3 |
8.5 |
|
|
|
|
2.4 |
6 |
|
|
|
|
1.3 |
2.9 |
|
|
|
Do the data show that there is a difference between some of the suppliers? Test at the 1% level
**********************************************************************
Let x1 = percentage difference of waste between the layout on the computer and the actual waste when the clothing is made (called run-up) from plant 1
Let x2 = percentage difference of waste between the layout on the computer and the actual waste of run-up from plant 2
Let x3 = percentage difference of waste between the layout on the computer and the actual waste of run-up from plant 3
Let x4 = percentage difference of waste between the layout on the computer and the actual waste of run-up from plant 4
Let x5 = percentage difference of waste between the layout on the computer and the actual waste of run-up from plant 5
Let μ1 = mean percentage difference of waste between the layout on the computer and the actual waste of run-up from plant 1
Let μ2 = mean percentage difference of waste between the layout on the computer and the actual waste of run-up from plant 2
Let μ3 = mean percentage difference of waste between the layout on the computer and the actual waste of run-up from plant 3
Let μ4 = mean percentage difference of waste between the layout on the computer and the actual waste of run-up from plant 4
Let μ5 = mean percentage difference of waste between the layout on the computer and the actual waste of run-up from plant 5
(vii) Calculate sample mean and sample standard deviation for Plant 4 sample
Enter sample mean in decimal form to nearest hundredth, then comma, then sample standard deviation in decimal form to nearest hundredth. Examples of correctly entered answers:
13.27,2.31
0.27,0.06
-10.30,0.79
(viii) Calculate sample mean and sample standard deviation for Plant 5 sample
Enter sample mean in decimal form to nearest hundredth, then comma, then sample standard deviation in decimal form to nearest hundredth. Examples of correctly entered answers:
13.27,2.31
0.27,0.06
-10.30,0.79
(ix) Using technology, determine F ratio test statistic and corresponding p-value.
Enter test statistic to nearest hundredth, then enter comma, then enter p-value to nearest thousandth. Examples of correctly entered responses:
12.33,0.004
7.50,0.000
6.77,0.504
Trending now
This is a popular solution!
Step by step
Solved in 5 steps
