Question

In: Statistics and Probability

How do I explain the following regression result in terms of the coefficients of each dependent...

How do I explain the following regression result in terms of the coefficients of each dependent variable on the independent variable which is revenue

SUMMARY OUTPUT
Regression Statistics
Multiple R 0.997839
R Square 0.995683
Adjusted R Square 0.990286
Standard Error 753750.6
Observations 10
ANOVA
df SS MS F Significance F
Regression 5 5.241E+14 1.048E+14 184.4968493 8.11978E-05
Residual 4 2.27256E+12 5.681E+11
Total 9 5.26373E+14
Coefficients Standard Error t Stat P-value Lower 95%
Intercept 1866377 824571.4499 2.2634507 0.086350341 -423000.5781
SQFT (x1) 186.4999 6.709995639 27.794335 9.96753E-06 167.8699299
Population (x2) 62.95023 5.336191975 11.796845 0.000295505 48.13458323
Manager A 4163155 636926.1245 6.5363225 0.002830839 2394764.135
Manager B 2109981 693293.1413 3.0434186 0.038273892 185090.9244
Manager C 2721259 800988.7528 3.3973752 0.027343382 497357.9826

Solutions

Expert Solution

The regression equation for the predicted variable revenue would be as follows:

Predicted Revenue = 1866337 + SQFT*(186.4999) + Population *(62.95023)+ Manager A *(4163155) + Manager B *(2109981) + Mnager C *(2721259)

Predicted Revenue is dependent of the coefficients as follows:

Intercept value is the minimum value revenue when all other variables are zero.

Every one unit change in SQFT, the predicted revenue would be changed by 186.4999 units

similarly, every one unit change in Population, the predicted Revenue would change by 62.95023 units

For every one unit change in Manager A, Manager B and Manager C, the predicted Revenu will be affected by 4163155, 2109981, 2721253 units respectively.

This is how we use coefficients in interpreting a regression equation.


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