Cascade Pharmaceuticals Company developed the following regression model, using time-series data from the past 33 quarters, for one of its nonprescription cold remedies:

Y=1.04+0.24X₁0.27X₂

Y=1.04+0.24X₁0.27X₂

where

Y

Y= quarterly sales (in thousands of cases) of the cold remedy

X₁X1= Cascade's quarterly advertising ( $1,000) for the cold remedy

X_2x2= competitors' advertising for similar products ( $10,000)

Here is additional information concerning the regression model:

sb1=0.042

sb1=0.042,s

b2

=0.090

sb2=0.090,R

2

=0.640

R2=0.640,s

e

=1.63

se=1.63,F-statistic=31.402

F-statistic=31.402, andDurbin-Watson(d)statistic=0.499

Durbin-Watson(d)statistic=0.499.

a. Which of the independent variables (if any) appears to be statistically significant (at the 0.05 level) in explaining sales of the cold remedy? (Hint:t

0.05/2,33-3

=2.042

t0.05/2,33-3=2.042.)Check all that apply.

X

1

X1

X

2

X2

b. What proportion of the total variation in sales is explained by the regression equation?

0.132

0.042

0.640

0.090

c. The given F-value shows that you can or can not reject the null hypothesis that neither of the independent variables explains a significant (at the 0.05 level) proportion of the variation in income. (Hint:F

0.05,2,33-2-1

=3.316

F0.05,2,33-2-1=3.316.)