Estimate of the variance in the electric power measurement

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Reference no: EM1384064

The electric power consumed each month by a chemical plant is thought to be related to the average ambient temperature (x₁), the number of days in the month (x₂), the average product purity (x₃), and the tons of product produced (x₄). The past year's historical data are available and are presented in the following table:

y	x₁	x₂	x₃	x₄
240	25	24	91	100
236	31	21	90	95
270	45	24	88	110
274	60	25	87	88
301	65	25	91	94
316	72	26	94	99
300	80	25	87	97
296	84	25	86	96
267	75	24	88	110
276	60	25	91	105
288	50	25	90	100
261	38	23	89	98

Fit a multiple linear regression model to this data. Determine whether or not the model you have assumed can be simplified by dropping any of the terms. Calculate the ANOVA table for the model, which you have determined. What is the estimate of the variance in the electric power measurement? Plot residual plots to determine if the assumptions underlying your analysis are met. Is this normal assumption a good one here? Calculate parameter covariance and parameter correlation matrix for your model. Do you have any concerns on the basis of this matrix?

Reference no: EM1384064

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