Use linear regression to predict the value at X=10. Independent Variable Dependent Variable о о л...
Regression analysis is used to: A. Predict the value of the dependent variable vased on the value of at least one independent variable B. Explain changes in an independent variable on the dependent variable C. It offers proof of causation D. A & B only E. A, B, & C
In a regression analysis, the variable that is used to predict the dependent variable a. is the independent variable b. must have the same units as the variable doing the predicting c. is the dependent variable d. usually is denoted by x
QUESTION 1 The Simple Linear Regression is fit or constructed to predict a dependent variable. True False QUESTION 2 The Coefficient of Determination is used to explain in what percent (%) the independent variable is affecting the dependent variable. True False
1. In multivariate regression: a) More than one independent variable is used to predict a single dependent variable b) The value of r gives you the slope c) More than one dependent variable is predicted by a single independent variable d) More regressions are necessary
The coefficient of a linear regression equation indicates Select one: a. the change in the dependent variable relative to a unit change in the independent variable. b. the change in the independent variable relative to a unit change in the dependent variable. c. the percentage change in the dependent variable relative to a unit change in the independent variable. d. the percentage change in the independent variable relative to a unit change in the dependent variable.
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 the mean value of the dependent variable is independent of variation in the independent variable, the slope of the regression line is a. zero. b. positive. c. negative. d. infinite.
A linear regression model found the following : Dependent variable : Quantity Independent variables : X1 X2 coefficient constant. 10 price. -2 Income. 3 R^2 = 0.83 t = 2.36 a. write the demand function as an equation b. do the sign of the coefficients make sense ? why? c. if price = 10, Income = 24 what is the predicted quantity sold? d. find the point price elasticity at price =10, Income = 24
The equation of the regression line between two variables x (independent variable) and y (dependent variable) is given by y-hat = -3x + 2; and the correlation coefficient is r = -.95. The possible x-values range from 1 to 10. Which of the following statements are correct? I. The variable y is strongly positive correlated to the variable x. II. The variable y is strongly negative correlated to the variable x. III. If x = 5, one would predict that...
*** Linear Regression Analysis *** Dependent Variable: Weight Loss (in Pounds) Independent variable: Exercise Time (in Minutes) Analysis of Variance Sum of Mean F p Source df Squares Square Ratio Value ------------------------------------------------------------------------- Regression 1 ___(b)___ 85.456 __ (e)__ .001 Residual __(a)__ 25.678 __(d)__ ------------------------------------------------------------------------- Total 11 ___(c)___ 3% Degree of Freedom for Residual = ____ TYPE YOUR ANSWER HERE: ____ 3% Sum of Squares Due to Regression = ____ TYPE YOUR ANSWER HERE: ____...