Exhibit 14-4
Regression analysis was applied between sales data (Y in $1,000s) and advertising data (x in $100s) and the following information was obtained. = 12 + 1.8 x
n = 17
SSR = 225
SSE = 75
S b1 = 0.2683
-Refer to Exhibit 14-4. The t statistic for testing the significance of the slope is
A)1.80
B)1.96
C)6.708
D)0.555

Question

Exhibit 14-4
Regression analysis was applied between sales data (Y in $1,000s) and advertising data (x in $100s) and the following information was obtained.  = 12 + 1.8 x
n = 17
SSR = 225
SSE = 75
S b1 = 0.2683
-Refer to Exhibit 14-4. The t statistic for testing the significance of the slope is
A)1.80 
B)1.96 
C)6.708 
D)0.555

Quizplus · Accepted Answer

To find the t statistic for testing the significance of the slope, we need to use the formula: t = b1 / (sqrt(S_b1 / (n-2))) where b1 is the slope coefficient, S_b1 is the residual sum of squares, and n is the sample size. Substituting the given values, we get: t = 1.8 / (sqrt(0.2683 / 15)) t = 6.708 The critical value for a two-tailed test at the 5% level of significance with 15 degrees of freedom is 2.131. Since the calculated t statistic (6.708) is greater than the critical value (2.131), we can reject the null hypothesis and conclude that the slope is statistically significant at the 5% level.

Exhibit 14-4 Regression Analysis Was Applied Between Sales Data (Y in $1,000s)