Lance is studying the relationship between sales training of the sales force and customer satisfaction and loyalty. When researchers like Lance are focused on explanation rather than prediction, then which of the following is most appropriate when using simple regression? A) standardized regression coefficient (b) B) Y-intercept a C) c² D) raw parameter estimates

Question

Quizplus · Accepted Answer

When researchers are focused on explanation rather than prediction, they are typically interested in understanding the relationship between two variables and identifying the strength and direction of this relationship. In this context, the most appropriate choice when using simple regression is the standardized regression coefficient (b). The standardized regression coefficient provides a measure of the strength and direction of the association between the predictor variable (in this case, sales training) and the outcome variable (in this case, customer satisfaction and loyalty), while controlling for the effects of other variables. This allows researchers to understand the unique contribution of the predictor variable to the outcome variable, and to compare the strengths of different predictors. The Y-intercept (a) is also important in simple regression, as it represents the value of the outcome variable when the predictor variable is equal to zero. However, in terms of understanding the relationship between predictor and outcome variables, the standardized regression coefficient is typically the most informative choice. The other options listed (c², raw parameter estimates) are not relevant or meaningful in this context.

Lance Is Studying the Relationship Between Sales Training of the Sales