Exam 15: Understanding Regression Analysis Basics

Assume you are developing a general conceptual model for the Advanced Automotive Concepts dataset.Which of the following variables would most likely be your dependent variable?

Which form of regression is useful when the researcher has many independent variables and wants to narrow the set down to a smaller number?

Once we establish,through multiple regression analysis,that certain independent variables are statistically significant in predicting a dependent variable,we may assume this relationship to be one of cause and effect.

When you have independent variables that are not significant in multiple regression analysis,it is appropriate to take them out and rerun the regression.The new model is referred to as a "trimmed" model.

There is a type of multiple regression,called stepwise multiple regression,that does the trimming operation automatically.

In the formula for bivariate regression analysis,the change in y for each one-unit change in x is known as the slope.

The multiple R,also called the coefficient of determination,in multiple regression ranges from 0 to +1.00 and represents the amount of the dependent variable "explained" by the combined independent variables.

A form of regression analysis where more than one independent variable is used in the regression equation is known as:

In regression,the line that runs through the points on a scatter diagram is positioned to minimize the vertical distances away from the line of the various points because of the least squares criterion.

Which statistic is used to determine whether or not multicollinearity is a concern in multiple regression?

Independent variables are normally measured in different units,so to determine the relative importance of the beta weights between independent variables we would use:

In bivariate regression,if the F value is significant (say .05 or less),then:

In bivariate regression analysis,the higher the Adjusted R Square value:

Stepwise multiple regression is useful if a researcher has many dependent variables but needs additional dependent variables in order to obtain a good predictive model.

In the formula for a straight line,the slope is defined as:

Which of the following are warnings that the textbook authors give regarding regression analysis?

The two ways of making a prediction are extension analysis and baseline predictive modeling.

While the scaling assumptions of multiple regression require that both the independent and dependent variables be at least interval-scaled,we may use nominal independent variables by using:

In regression,the variable being predicted,b,is known as the dependent variable.

In regression,the variable being predicted,y,is known as the dependent variable.