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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