Which of the following is not the explained variance?1 pointThe degree to which the regression equation of X and Y is better at predicting the dependent variable than the average of Y.The percentage of variance in Y that is explained by the mean of X.The percentage of the variance in Y which isexplained with the regression equation.The Pearson r squared.

A regression model summary had the results (R = .63, R2 = .40). This model explained 40% of the variance in a customs agent’s decision to search a traveller for drugs. How much variance in a customs agent’s decision to search a traveller for drugs was due to error?

Question 1: In a regression analysis, what information gives R²?a) The unexplained variance by the predictorsb) The share of the dependent variable variance explained by the predictorsc) The badness of the fitd) The quality of the data selection

Assuming a linear relationship between X and Y, if the coefficient of correlation (r) equals – 0.30, A. the variance of X is negative. B. variable X is larger than variable Y.                          C. there is no correlation.                                      D.  the slope (b1) is negative.

Which statement about the coefficient of determination (R^2) is true?It represents the slope of the regression line.It indicates the percentage of the variance in the dependent variable that is predictable from the independent variable.It can take on any value between -1 and 1.It is the square root of the correlation coefficient.

When conducting a regression analysis, what does the coefficient of determination (R-squared) represent?  A. The strength of the relationship between variables  B. The predicted values of the dependent variable  C. The slope of the regression line  D. The proportion of variance in the dependent variable explained by the independent variable