Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained. = 12 + 1.8x

N = 17
SSR = 225
SSE = 75
Sb₁ = .2683

To perform an F test, the p-value is

Question

Regression analysis was applied between sales data (y in $1000s) and advertising data (x in $100s) and the following information was obtained.

= 12 + 1.8x

N = 17
SSR = 225
SSE = 75
Sb₁ = .2683

To perform an F test, the p-value is

Quizplus · Accepted Answer

To perform an F test, we need to calculate the test statistic and find its p-value. The test statistic is calculated as:

F = (SSR/1) / (SSE/(n-2))

where SSR is the sum of squares regression, SSE is the sum of squares error, and n is the sample size. Plugging in the given values, we get:

F = (225/1) / (75/15) = 15

Using a calculator or F-table, we find that the p-value for this F statistic is much less than .01, indicating strong evidence against the null hypothesis (that there is no linear relationship between sales and advertising). Therefore, the answer is A, the p-value is less than .01.

Regression Analysis Was Applied Between Sales Data (Y in $1000s)