Considering a regression model of the assessed values of small office buildings, measured in thousands of dollars (Assessed). The independent variables being considered are square feet of floor space (Floor), number of offices (Offices), and number of customer entrances (Entrances). The data set is shown below and is included in the answer file.

a. Find the least squares fit using these three independent variables. Write your estimated regression equation.

b. Interpret the p-value of the F-statistic. What is the null hypothesis? What is your conclusion?

c. Use your results to do a two-tailed t-test on the significance of each of the slopes. State the hypothesis. Interpret the p-values; what are your conclusions for each slope?

d. Interpret the R-squared value. Is the model’s fit good enough to be of practical value?

See Excel file for the data and specific answers I need help on. Thanks!

a. Find the least squares fit using these three independent variables. Write your estimated regression equation.

b. Interpret the p-value of the F-statistic. What is the null hypothesis? What is your conclusion?

c. Use your results to do a two-tailed t-test on the significance of each of the slopes. State the hypothesis. Interpret the p-values; what are your conclusions for each slope?

d. Interpret the R-squared value. Is the model’s fit good enough to be of practical value?

See Excel file for the data and specific answers I need help on. Thanks!

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