Option c) is correct.
c. more than one independent variable |
Multiple regression analysis
one dependent variable and more than one independent variable
A multiple regression model has _____. a. at least two dependent variables b. more than one...
How does a bivariate regression model differ from a multiple regression model? Multiple Choice A bivariate regression has only one dependent and independent variable but a multiple regression has one dependent variable and may have many independent variables. A bivariate regression has more than one dependent variable and only one independent variable where a multiple regression has one dependent variable and may have many independent variables. A bivariate regression has only one dependent and many independent variables but a multiple...
What is a multiple regression equation? (Select all that apply) a. One that represents the mathematical effect that several independent variables have on the dependent variable b. One in which the x-values are multiplied by one another c. One that explains more of the variance in y than does a single linear regression equation d. An experimental model for determining best practices e. One that uses more than one predictor variable to predict the value of the outcome variable f....
1. In order to test whether the multiple linear regression model y bo +b,x1 + b2X2 is better than the average model (lazy model), which of the following null hypotheses is correct: a. Ho' b1 = b2 = 0 Но: B1 B2-0 с. We have a dataset Company with three variables: Sales, employees and stores. To build a multiple linear regression model using Sales as dependent variable, number of stores and number of employees as independent variables, which of the...
For two valid regression models which have same dependent variable, if regression model A and regression model B have the followings, Regression A: Residual Standard error = 30.33, Multiple R squared = 0.764, Adjusted R squared = 0.698 Regression B: Residual Standard error = 40.53, Multiple R squared = 0.784, Adjusted R squared = 0.658 Then which one is the correct one? Choose all applied. a. Model A is better than B since Model A has smaller residual standard error...
29 in multiple regression ana 15:3 B) The # there can be any number of dependent variables but only one in de pendent variable coefficient of determination musth be larger than 1 can be several independent variables but only one one de pendent variable o there ther must be only one idenpendent variable
When two or more independent variables in the same regression model can predict each other better than the dependent variable, the condition is referred to as ____. Autocorrelation Multicollinearity Heteroscedasticity Homoscedasticity
8. In linear regression, the confidence interval can be wider than the prediction interval. a. True b. False 9. In a regression and correlation analysis if R-1, then a. SSg - SSI b. SSg - 1 c. SSR ESSE d. SSR SS 10. A multiple regression model has: a. only one independent variable b. more than one dependent variable c. more than one independent variable d. none of the above
Regression and Multicollinearity When multiple independent variables are used to predict a dependent variable in multiple regression, multicollinearity among the independent variables is often a concern. What is the main problem caused by high multicollinearity among the independent variables in a multiple regression equation? Can you still achieve a high r for your regression equation if multicollinearity is present in your data? Regression and Multicollinearity When multiple independent variables are used to predict a dependent variable in multiple regression, multicollinearity...
When evaluating a multiple regression model, for example when we regress dependent variable Y on two independent variables X1 and X2, a commonly used goodness of fit measure is: A. Correlation between Y and X1 B. Correlation between Y and X2 C. Correlation between X1 and X2 D. Adjusted-R2 E. None of the above
How does a regression plane differ from a regression line? Multiple Choice A regression plane represents a two-dimensional space (e.g. one dependent and one independent variable) whereas a regression line represents a three-dimensional space (e.g. one dependent and two independent variables). A regression plane represents a three-dimensional space (e.g. one dependent and two independent variables) whereas a regression line represents a two-dimensional space (e.g. one dependent and one independent variable). A regression plane can represent a bivariate regression model and...