In: Math
A company would like to estimate its total cost equation. It has collected 48 months of monthly production output and corresponding total production costs. The collected data is in the file Production Cost Data Only.xlsx. Recall that
TOTAL COST = Fixed Costs + Variable Cost per Unit *Output.
Use the data to estimate a function that describes total cost for this company. (Round answers to 2 decimal places)
Develop a scatterplot of the two variables: monthly output and monthly total costs. Describe the relationship.
Estimate a total cost curve for this company. State the estimated total cost function.
Based on your estimated total cost curve what is the estimated Fixed Cost for the Company?
Based on your estimated total cost curve what is the estimated average unit variable cost for the Company?
Develop a 95% confidence interval for the true average variable cost per unit.
What percent of the variation in monthly production costs is “explained” by the monthly production output?
Suppose the plant manager is interested in mean costs for several monthswhere output averages 30,000 units (i.e., Xp = 30). What is the predicted monthly total costs when output averages 30? Construct a 95% confidence interval for the mean production costs for months that average 30,000 units of output.
Monthly Output (in thousands of units) | Monthly Total Production Cost (in thousand $) |
47 | 926 |
45 | 888 |
42 | 841 |
43 | 888 |
42 | 863 |
42 | 898 |
41 | 885 |
48 | 911 |
41 | 812 |
40 | 837 |
39 | 845 |
39 | 856 |
40 | 858 |
38 | 852 |
39 | 877 |
39 | 926 |
37 | 915 |
37 | 841 |
37 | 812 |
37 | 833 |
36 | 822 |
38 | 809 |
37 | 769 |
38 | 783 |
41 | 745 |
38 | 716 |
39 | 656 |
39 | 620 |
37 | 616 |
35 | 771 |
34 | 754 |
34 | 703 |
32 | 667 |
31 | 643 |
28 | 540 |
25 | 502 |
20 | 436 |
17 | 380 |
14 | 314 |
13 | 294 |
10 | 290 |
10 | 190 |
9 | 203 |
8 | 176 |
8 | 192 |
6 | 149 |
5 | 114 |
4 | 126 |
SUMMARY OUTPUT | ||||||
Regression Statistics | ||||||
Multiple R | 0.970683724 | |||||
R Square | 0.942226892 | |||||
Adjusted R Square | 0.940970955 | |||||
Standard Error | 64.25220388 | |||||
Observations | 48 | |||||
ANOVA | ||||||
df | SS | MS | F | Significance F | ||
Regression | 1 | 3097160.098 | 3097160.098 | 750.2182035 | 3.98347E-30 | |
Residual | 46 | 189903.9024 | 4128.345704 | |||
Total | 47 | 3287064 | ||||
Coefficients | Standard Error | t Stat | P-value | Lower 95% | Upper 95% | |
Intercept | 38.24585352 | 24.28492378 | 1.574880526 | 0.122137456 | -10.63716267 | 87.12886971 |
Monthly Output | 19.68525619 | 0.718699384 | 27.39011142 | 3.98347E-30 | 18.23858937 | 21.13192302 |
Develop a scatterplot of the two variables: monthly output and monthly total costs. Describe the relationship.
Estimate a total cost curve for this company. State the estimated total cost function.
Total cost = 38.2459 + 19.6853 * monthly output
Based on your estimated total cost curve what is the estimated Fixed Cost for the Company?
Fixed cost = intercept = 38.2459
Based on your estimated total cost curve what is the estimated average unit variable cost for the Company?
= average unit variable cost = slope = 19.6853
Develop a 95% confidence interval for the true average variable cost per unit.
95% confidence interval for slope =(18.2386,21.1319)
What percent of the variation in monthly production costs is “explained” by the monthly production output?
R^2 = 0.942226892