A multiple regression analysis produced the following tables: Predictor Coeffici

ID: 3268621 • Letter: A

Question

A multiple regression analysis produced the following tables:

Predictor Coefficients Standard Error t Statistic p-value

Intercept 752.0833 336.3158 2.236241 0.042132

x1 11.87375 5.32047 2.031711 0.082493

x2 1.908183 0.662742 2.879226 0.01213

Source df SS MS F p-value

Regression 2 203693.3 101846.7 6.745406 0.010884

Residual 12 181184.1 15098.67

Total 14 384877.4

These results indicate that:

Question 8 options:

1) none of the predictor variables are significant at the 5% level

2) each predictor variable is significant at the 5% level

3) x1 is the only predictor variable significant at the 5% level

4) x2 is the only predictor variable significant at the 5% level

5) the intercept is not significant at the 5% level

We know if p value is less than (or equal to) alpha(here 0.05), then the null hypothesis is rejected in favour of the alternative hypothesis.

Here

H0 : intercept=0, vs intercept not equal to 0

H1 : beta1 (coefficient of X1) = 0, vs beta1 not equal to 0

H2 : beta 2 (coefficient of X2) = 0 vs beta 2 not equal to 0

Here option 4 is correct because p value for the coefficient of X2 is less than 0.05 where as pvalue of coefficient of X1 is greater than 0.05.

Here intercept is also significant.