Question

a sales manager for an advertising agency believes there is a relationship between the number of contacts that a salesperson makes and the amount of sales dollars earned. a regression anova shows the following results:anova dfssmsfsignificance fregression1.0013,555.4213,555.42156.380.00residual8.00693.4886.68 total9.0014,248.90 what is the value of the standard error of estimate?

Answer 1

The standard error of estimate is calculated by taking the square root of the mean square error, which is obtained by dividing the sum of squares due to error by the degrees of freedom for residuals. In this case, it is the square root of 86.685, resulting in approximately 9.31.

Step-by-step explanation:

The question asks how to find the standard error of estimate given an ANOVA table from a regression analysis. To find the standard error of estimate (SEE), also known as the standard error of the regression, we need to take the square root of the mean square error (MSE) from the residuals. The MSE is found by dividing the sum of squares due to error (SSE) by the residual degrees of freedom (df).

In the provided ANOVA table, we have a SSE (sum of squares due to error) of 693.48 and df of 8 for the residual. Therefore, the calculation for SEE is the square root of MSE, which is the square root of 693.48 / 8.

SEE = √(693.48 / 8)
SEE = √(86.685)
SEE = 9.31 (rounded to two decimal places)