(1) a = round to 2 decimal places (2) c= (3) d= (4) e= (5) f= round to 2 decimal
ID: 3219329 • Letter: #
Question
(1) a =
round to 2 decimal places
(2) c=
(3) d=
(4) e=
(5) f=
round to 2 decimal places
(6) g=
round to 2 decimal places
(7) h=
round to 2 decimal places
(8) i=
round to 2 decimal places
**If you could also provide brief explanations.**
SUMMARY OUTPUT Regression Statistics Multiple R 0.744152817 R Square Adjusted R Square b Standard Error 16.50688387 Observations 50 ANOVA Significance MS 1.75489E-07 Regression Residual 12261.47468 Total 27477.52 Standard p-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Coefficients Error t Stat Intercept 0.06890345 9.84254853. -0.00700057 0.99444534 19.8928138. 19.755006 19.8928138 19.7550069 Age 1.72515290 0.26509485 6.50768148 5.4911E-08 1.19122445 2.2590813 1.19122445 2.25908136 Head -15.0857438 5.12089660 2.94591846 0.00503999 25.3997598 4.7717286 25.399759 -4.77172867 28.6724871 8.1166889 3.53253490 0.00064386 -45.0203375 12.324636 45.0203375 12.3246363 Manager Sales 17.4212921 6.2358485 2.79373240 0.00762356 29.980939 -4.8616484 29.9809359 -4.8616484Explanation / Answer
a = R squared = ( SS(Total) - SS(Residual) ) / SS(Total) = (27477.52 - 12261.47468)/27477.52 = 0.5538 = 55.38%
c = df(Regression) = # of predictor variables = 4
e = df(Total) is one less than the sample size = 50 - 1 = 49
d = df(Residual) = df(Total) - df(Regression) = 49-4 = 45
f = SS(regression) = SS(Total) - SS(error) = 27477.52 - 12261.47468 = 15216.05
g = MS(regression) = SS(regression)/df(regression) = 15216.04532/4 = 3804.01
i = MS(Residual) = SS(Residual)/df(Residual) = 12261.47468/45 = 272.48
h = F = MS(Regression)/MS(residual) = 3804.01133/272.4772151 = 13.96
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