A multiple linear regression model of the following form is fitted to a data set
Yi = ̠0 + ̠1xi1 + ̠2xi2 + ̠3xi3 + ̡i, ̡i ~ N(0, ̣2)i.i.d.
The model is fitted using SAS and the following output is obtained:
Source DF Sum of Squares Mean Square F Value Pr > F
Model 3 2667.79 889.26 ? < 0.0001
Error 9 47.97 ?
Corrected Total 12 2715.76
Variable Parameter Estimate Standard Error t Value Pr > |t|
Intercept 71.648 14.142 5.07 0.0007
x1 1.452 0.117 12.41 < .0001
x2 0.416 0.186 2.24 0.0517
x3 -0.237 0.173 ? 0.2054
(a) Find the sample size.
(b) Find MSE.
(c) Find R2 and explain it’s meaning.
(d) Find adjusted R2.
(e) Find the value for the F-test statistic.
(f) What hypotheses the F-test? Please set up the null hypothesis and alternative hypothesis.
(g) Given ̱ = 0.05, what conclusion will you have for the above test?
(h) One wish to test H0 : ̠3 = 0 vs Ha : ̠3 ≠ 0. Please calculate the test statistic.