A utility company would like to predict the monthly heating bill for a household

Question

A utility company would like to predict the monthly heating bill for a household in a certain county in January. A random sample of households in the county was selected and their January heating bill was recorded along with the variables SF, Age, and Temp, with the results shown in the accompanying regression output. Complete parts a and b below SF: the square footage of the house Age: the age of the current heating system, in years Temp: the thermostat setting, in degrees Fahrenheit, during the day ANOVA df Regression Residual Total 3 102902.8506 61598.8324 31 164501.6830 28 Coefficients Standard Erro - 651.4034 0.0935 2.0455 10.8701 322.5241 0.0208 1.5023 5.0059 Intercept SF Temp a. Test the signicance of each independent variable using a-0.01.Forb, and p,Jetjs 1 represent the varable SF, etj 2represent the variable Age, and letj-3 represent the variable Temp. Test the significance of the variable SF. Determine the null and alternative hypotheses. a. Determine the test statistic for the variable SF b. Determine the P-value using alpha-0.10 c. Determine the test statistic for the variable Age d. Find P-value using alpha -0.10

Explanation / Answer

a) Test Statistic for SF = 0.0935/0.0208 = 4.495

b) P value = P(t>4.495) = 0.000

c) Test Statistic for SF =2.0455/1.5023 = 1.362

d) P value = P(t>1.362)

= 0.183

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