The production levels of a finished product (produced from sheets of stainless steel) have varied quite a bit, and management is trying to devise a method for predicting the daily amount of finished product. The ability to predict production is useful for scheduling labor, warehouse space, shipment of raw materials, and also to suggest pricing strategy.
The number of units of the product that can be produced in a day depends on the width and density of the sheets being processed, and the tensile strength of the steel. The data are taken from 20 days of production. Observations can be found on page 2 of Excel workbook Homework
7.a. Does there exist multicollinearity between the predictor variables? (Compute the correlation matrix.)
b. Run a multiple regression analysis. Use α = 0.05.
i. How much of the variability in units produced is explained by the model?
ii. Refer to the ANOVA table and write out the hypothesis being tested, the test statistic,the critical value, the p-value and the conclusion.
iii. Write out the estimated regression equation.
iv. What independent variable(s) are statistically significant for this model? (Provide p-values)

Obs	Units of Product	Width	Density	Tensile Strength
1	763	19.8	128	86
2	650	20.9	110	72
3	55	15.1	95	62
4	742	19.8	123	82
5	470	21.4	77	52
6	651	19.5	107	72
7	756	25.2	123	84
8	563	26.2	95	83
9	681	26.8	116	76
10	579	28.8	100	64
11	716	22	110	80
12	650	24.2	107	71
13	761	24.9	125	81
14	549	25.6	89	61
15	641	24.7	103	71
16	606	26.2	103	67
17	696	21	110	77
18	795	29.4	133	83
19	582	21.6	96	65
20	559	20	91	62

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a To determine if there exists multicollinearity between the predictor variables we can compute the ... View the full answer