MINITAB was used to fit the model y = 0 + 1 x1 + 2 x2 + to n = 20 data points, and

MINITAB was used to fit the model y = β0 + β1 x1 + β2 x2 + ε to n = 20 data points, and the printout (top of page 628) was obtained.

a. What are the sample estimates of β0, β1, and β2?

b. What is the least squares prediction equation?

c. Find SSE, MSE, and s. Interpret the standard deviation in the context of the problem.

d. Test H0: β1 = 0 against Ha: β1 ‰  0. Use α = .05.

e. Use a 95% confidence interval to estimate β2.

f. Find R2 and R2a and interpret these values.

g. Use the two formulas given in this section to calculate the test statistic for the null hypothesis H0: β1 = β2 = 0.

Compare your results with the test statistic shown on the printout.
h. Find the observed significance level of the test you conducted in part g. Interpret the value.

The regression equation is Y 506.35-941.9 XI - 429.1 X2 Coet SE Coet Predictor Constant 506.346 5 X1 X2 11.21 0.000 -941.900 275.08 3.42 0.003 -429.060 379.831.13 0.274 S-94.251 R-sq-45.9 R-Sq (adj) -39.6 Analysis of Variance source Regression Residusl Er 17 151016 5883 Total DF NS 2265 .2 0.00s 19 279345