Regression Analysis
- The chief executive officer for Floor Covering Mills, Inc., wants to develop a regression model to predict the monthly profit of the company (in thousands of dollars) from the units of the product that the firm produces (in thousands of units). Data were collected for 15 months when the production level was varied and are presented in the accompanying table. Apparently, if the production level is too high, the amount of inventory increases and the profits decrease.
|
Profit |
Production |
|
3.5 |
0.0 |
|
24.4 |
0.5 |
|
36.1 |
1.0 |
|
26.5 |
1.5 |
|
30.6 |
2.0 |
|
39.3 |
2.5 |
|
55.6 |
3.0 |
|
56.6 |
3.5 |
|
64.8 |
4.0 |
|
63.4 |
4.5 |
|
57.8 |
5.0 |
|
55.2 |
5.5 |
|
54.9 |
6.0 |
|
59.6 |
6.5 |
|
62.7 |
7.0 |
- Find the estimated regression equation. Which type of regression model did you use?
- Predict the profit level for a production level of 5000 (5.0 in our units).
- Plot the estimated profit equation, and from the plot, determine the production level that maximizes profit.
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