A production plant cost-control engineer is responsible for cost reduction. One of the costly items in theplant is the amount of water used by the production facilities each month. The engineer decides to investi-gate water usage by collecting seventeen observations on the plant's monthly water usage (in gallons) andother variables. Run a regression where water usage is the dependent variable and temperature (averagemonthly temperature in Fahrenheit), production in 1000 pounds, days (Number of plant operating days inthe month), and persons (Number of persons on the monthly plant payroll) are independent variables. Inter-pret all relevant output.

Question
Asked Dec 14, 2019
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temp prod days persons water
58.8 7107 21 129 3067
65.2 6373 22 141 2828
70.9 6796 22 153 2891
77.4 9208 20 166 2994
79.3 14792 25 193 3082
81 14564 23 189 3898
71.9 11964 20 175 3502
63.9 13526 23 186 3060
54.5 12656 20 190 3211
39.5 14119 20 187 3286
44.5 16691 22 195 3542
43.6 14571 19 206 3125
56 13619 22 198 3022
64.7 14575 22 192 2922
73 14556 21 191 3950
78.9 18573 21 200 4488
79.4 15618 22 200 3295
A production plant cost-control engineer is responsible for cost reduction. One of the costly items in the
plant is the amount of water used by the production facilities each month. The engineer decides to investi-
gate water usage by collecting seventeen observations on the plant's monthly water usage (in gallons) and
other variables. Run a regression where water usage is the dependent variable and temperature (average
monthly temperature in Fahrenheit), production in 1000 pounds, days (Number of plant operating days in
the month), and persons (Number of persons on the monthly plant payroll) are independent variables. Inter-
pret all relevant output.
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A production plant cost-control engineer is responsible for cost reduction. One of the costly items in the plant is the amount of water used by the production facilities each month. The engineer decides to investi- gate water usage by collecting seventeen observations on the plant's monthly water usage (in gallons) and other variables. Run a regression where water usage is the dependent variable and temperature (average monthly temperature in Fahrenheit), production in 1000 pounds, days (Number of plant operating days in the month), and persons (Number of persons on the monthly plant payroll) are independent variables. Inter- pret all relevant output.

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Expert Answer

Step 1

The null and alternative hypotheses are stated below:

Null hypothesis: The model is ineffective.

Alternative hypothesis: The model is effective.

Step 2

Step-by-step procedure to obtain the model using MINITAB is as follows:

  • Choose Stat > Regression > Regression.
  • In Response, enter the variable Water.
  • In Predictors, enter the variables temp...
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Regression Analysis: water versus temp, prod, days, persons Analysis of Variance Adj MS F-Value P-Value 612209 Adj SS 4 2448834 Source DF 9.88 Regression 0.001 0.02 temp 447803 447803 7.22 prod 1339312 1339312 21.61 0.001 days 431394 431394 6.96 0.022 556032 556032 8.97 0.011 persons Error 12 743798 61983 Total 16 3192632 Model Summary R-sq(ad) R-sq(pred) R-sq 248.964 76.70% 68.94% 59.74% Coefficients SE Coef Coef T-Value P-Value Term VIF 4.84 Constant 6360 1314 02 temp prod days 13.87 5.16 2.69 1.25 6.66 0.2117 0.0455 4.65 0.001 1.27 -126.7 48 -2.64 0.022 -21.82 7.28 -3 0.011 6.63 persons Regression Equation 6360 + 13.87 temp + 0.2117 prod - 126.7 days - 21.82 persons water

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