Average_Cost_($/unit)	Material_Cost_($/unit)	Plant	Plant_Dummy	Plant_Dummy*Material_Cost
37.12	1.1776	New	1	1.1776
30.86	0.8591	Old	0	0
35.02	1.9581	New	1	1.9581
42.64	2.0733	Old	0	0
43.32	2.1698	New	1	2.1698
42.61	1.4286	Old	0	0
43.22	3.3642	New	1	3.3642
43.17	2.3238	Old	0	0
44.45	3.8187	New	1	3.8187
34.07	1.8369	Old	0	0
41.21	4.7357	New	1	4.7357
40.66	2.5069	Old	0	0
47.19	5.2377	New	1	5.2377
43.37	1.5158	Old	0	0
45.77	5.7391	New	1	5.7391
44.15	4.3596	Old	0	0
47.13	6.2888	New	1	6.2888
46.88	7.0486	Old	0	0
50.58	7.4823	New	1	7.4823
42.51	1.4827	Old	0	0

Transcribed Image Text:

A company manufactures custom metal blanks. This analysis considers the factors that affect the cost to manufacture these blanks. The data, available below, were sampled from the accounting records of 20 previous orders filled during the last three months. The data measure performance at two plants, identified as "Old" and "New" in the column Plant. Complete parts (a) through (e) below. Click the icon to view the data table. (a) Would it be appropriate for management to compare the two plants using a two-sample comparison of the costs per unit, or would such a comparison be confounded by different material costs per unit in the two plants? OA. A two-sample comparison would be appropriate. Since the mean cost and standard deviation are the same for each group (costs are paired between the two plants), material cost per unit cannot be a confounding variable. OB. A two-sample comparison would be appropriate. Since the cost is not related to the material cost per unit, machine use per unit cannot be a confounding variable. OC. A two-sample comparison would not be appropriate. Since the cost is related to the material cost per unit, machine use per unit is a confounding variable. OD. A two-sample comparison may not be appropriate. Since the mean cost and standard deviation differ for the two groups, machine use may be a confounding variable. (b) Perform the two-sample t-test to compare the average cost per unit at the two plants for a = 0.05. Summarize this analysis, assuming that there are no lurking variables. Find the sample statistic, x₁-x₂. Let sample 1 correspond to the old plant and sample 2 correspond to the new plant. X₁ X₂= (Round to three decimal places as needed.) 4- Determine the two-sample t-statistic. t= (Round (Round to three decimal places as needed.) Identify the p-value. p-value = (Round to three decimal places as needed.) Determine the conclusion for this test. The p-value is the null hypothesis. There is ▼ evidence to conclude that there is a difference in the average cost per unit at the two plants. (c) Compare the average cost per unit at the two plants using an analysis of covariance with a = 0.05. Summarize the comparison based on this analysis. Represent these categories using a dummy variable coded as 1 if the plant is new. (Assume for the moment that the model meets the conditions for the MRM.) ▼statistically significant, meaning that the two plants xx, 50 The interaction in the model cost per unit for the new plant. (d) Compare the results from parts (b) and (c). Do they agree? You should take into account the precision of the estimates and your answer to part (a). Part (b) indicates that there is results ▼ different average costs per unit. The average cost per unit for the old plant ▾ evidence that there is a difference in the average cost per unit, while part (c) indicates that the two plants M (e) Does the estimated multiple regression used in the analysis of covariance meet the similar variances condition? O A. Yes; the variance for the average cost per unit are less than 1 for each plant. OB. No; the residuals for the new plant vary more than the residuals for the old plant. OC. No; the residuals for the old plant vary more than the residuals for the new plant. O D. Yes; there is insufficient evidence that the variances for the two plants are different. the average ▼ different average costs per unit. Therefore, the A company manufactures custom metal blanks. This analysis considers the factors that affect the cost to manufacture these blanks. The data, available below, were sampled from the accounting records of 20 previous orders filled during the last three months. The data measure performance at two plants, identified as "Old" and "New" in the column Plant. Complete parts (a) through (e) below. Click the icon to view the data table. (a) Would it be appropriate for management to compare the two plants using a two-sample comparison of the costs per unit, or would such a comparison be confounded by different material costs per unit in the two plants? OA. A two-sample comparison would be appropriate. Since the mean cost and standard deviation are the same for each group (costs are paired between the two plants), material cost per unit cannot be a confounding variable. OB. A two-sample comparison would be appropriate. Since the cost is not related to the material cost per unit, machine use per unit cannot be a confounding variable. OC. A two-sample comparison would not be appropriate. Since the cost is related to the material cost per unit, machine use per unit is a confounding variable. OD. A two-sample comparison may not be appropriate. Since the mean cost and standard deviation differ for the two groups, machine use may be a confounding variable. (b) Perform the two-sample t-test to compare the average cost per unit at the two plants for a = 0.05. Summarize this analysis, assuming that there are no lurking variables. Find the sample statistic, x₁-x₂. Let sample 1 correspond to the old plant and sample 2 correspond to the new plant. X₁ X₂= (Round to three decimal places as needed.) 4- Determine the two-sample t-statistic. t= (Round (Round to three decimal places as needed.) Identify the p-value. p-value = (Round to three decimal places as needed.) Determine the conclusion for this test. The p-value is the null hypothesis. There is ▼ evidence to conclude that there is a difference in the average cost per unit at the two plants. (c) Compare the average cost per unit at the two plants using an analysis of covariance with a = 0.05. Summarize the comparison based on this analysis. Represent these categories using a dummy variable coded as 1 if the plant is new. (Assume for the moment that the model meets the conditions for the MRM.) ▼statistically significant, meaning that the two plants xx, 50 The interaction in the model cost per unit for the new plant. (d) Compare the results from parts (b) and (c). Do they agree? You should take into account the precision of the estimates and your answer to part (a). Part (b) indicates that there is results ▼ different average costs per unit. The average cost per unit for the old plant ▾ evidence that there is a difference in the average cost per unit, while part (c) indicates that the two plants M (e) Does the estimated multiple regression used in the analysis of covariance meet the similar variances condition? O A. Yes; the variance for the average cost per unit are less than 1 for each plant. OB. No; the residuals for the new plant vary more than the residuals for the old plant. OC. No; the residuals for the old plant vary more than the residuals for the new plant. O D. Yes; there is insufficient evidence that the variances for the two plants are different. the average ▼ different average costs per unit. Therefore, the

Answer rating: 100% (QA)

a The appropriate option is C A twosample comparison would not be appropriate because the cost is related to the material cost per unit making machine ... View the full answer