4. Florida Power and Light Company want to forecast the monthly heating and light bill for households in Florida for the

[answerhappygod]

4 Florida Power And Light Company Want To Forecast The Monthly Heating And Light Bill For Households In Florida For The 1 (219.59 KiB) Viewed 26 times

4. Florida Power and Light Company want to forecast the monthly heating and light bill for households in Florida for the month of April. A random sample of Florida households was selected for the month of April their heating and light costs were recorded. Additionally, the following data for each household was recorded: SF: Square footage of the home. Age: Age of the heating and gas system measure in years. Temp: Thermostat setting in degrees Fahrenheit over a 24-hour period. FP&L decide to run a multiple linear regression using Excel. An Excel regression output was produced and the following statistics were found. ANOVA Table Regression Residual/Error Total df 3 28 31 SS 102454..9381 61158.5619 163613.5000 Regression Table Estimated Coefficient Intercept -652.2924 SF + 0.0904 Age + 2.0450 Temp + 10.8250 Standard Error 322.0966 0.0210 1.5089 5.0068 a. Interpret each of the estimated regression coefficients (what do the coefficients mean)? b. Compute the coefficient of determination, R2. Interpret the RP. c. Test whether each of the estimated regression coefficients are statistically significant a the 5% level of significance, a = 0.05. Remember t = b/se(b) d. Construct a global test of hypothesis that jointly each of he estimated regression coefficients are equal to zero. (hint think an F-statistic). e. Forecast/predict the FP&L bill given the following: SF = 2500 sq. ft. Age = 9 years Temp = 78 degrees Fahrenheit f. Construct a 95% confidence interval around the estimated regression coefficient on Age.