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# a. write your regression equation: b. p-value of F-stat is hypothesis is interpretation/conclusion: c. Hypothesis is interpretation of

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. write your regression equation: b. p-value of F-stat is hypothesis is interpretation/conclusion: c. Hypothesis is Floor: Offices: Entrances: e. Interpretation of R-squared; is model good enough to be useful? Yes or no Assessed Floor Offices Entrances 1796 4790 4 2 1544 4720 3 2 2094 5940 4 2 1968 5720 4 2 1567 3660 3 2 1878 5000 4 2 949 2990 2 1 910 2610 2 1 1774 5650 4 2 1187 3570 2 1 1113 2930 3 2 671 1280 2 1 1678 4880 3 2 710 1620 1 2 678 1820 2 1 1585 4530 2 2 842 2570 2 1 1539 4690 2 2 433 1280 1 1 1268 4100 3 1 1251 3530 2 2 1094 3660 2 2 638 1110 1 2 999 2670 2 2 653 1100 1 1 1914 5810 4 3 772 2560 2 2 890 2340 3 1 1282 3690 2 2 1264 3580 3 2 1162 3610 2 1 1447 3960 3 2 interpretation of p-value/conclusion of two-tailed test on each slope

Assesed= 33.55627 +.2444*floor +81.71365*Ofiices +84.61557*Entrances
b. p-value of F-stat is
1.1E-018
hypothesis is
H0: the coeggicients are all equal to 0 H1:...

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