34. In multiple regression, the multiple Rsq uare (also known as the coefficient of determination} can be interpreted as: a. reecting the degree of association between the dependent variable and the independent variables b. the percentage of total variation in Y explained by the independent variables c. a measure of the accuracy of the prediction, i.e., the range of error around forecasting the dependent variable d. all the independent variables are highly significant in forecasting the dependent variable 35. In multiple regression, the Fvalues can be interpreted as: a. reflecting the degree of association between the dependent variable and the independent variables b. the percentage of total variation in Y explained by the independent variables c. a measure of the accuracy of the prediction, i.e., the range of error around forecasting the dependent variable d. all Ithe independent variables are highly signicant in forecasting the dependent variable 36. In multiple regression, the Rivalues below .2 suggest: a. good predictive power b. excellent predictive power c. poor forecasting power d. modest predictive power 37. In multiple regression, the szaiues between .2 and .5 suggest: a. good predictive power b. excellent predictive power c. poor forecasting ability d. modest predictive power 38. In multiple regression, the szalues between .5to J5 suggest: a. good predictive power b. excellent predictive power c. poor forecasting power d. modest predictive power 39. In multiple regression, the Rivalues above .80 suggest; a. good predictive power b. excellent predictive power c. poor forecasting power d. modest predictive power 4!]. A is a "financial sales plan outlining how to allocate resources and selling efforts to achieve the sales forecast." a. sales forecast b. sales quota c. sales budget d. sales audit