Multiple Regression Analysis: without Dummy
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In simple linear regression, r 2 is the _____. a. coefficient of determination b. coefficient of correlation c. estimated regression equation d. sum of the squared residuals A least squares regression line ______. a. may be used to predict a value of y if the corresponding x value is given b. implies a cause-effect relationship between x and y c. can only be determined if a good linear relationship exists between x and y d. All of the answers are correct. Regression analysis was applied between sales (in $1000s) and advertising (in $100s), and the following regression function was obtained. = 80 + 6.2x Based on the above estimated regression line, if advertising is $10,000, then the point estimate for sales (in dollars) is _____. a. $700,000 b. $700 c. $142,000 d. $62,080 In a regression analysis, the variable that is used to predict the dependent variable ______. a. is the dependent variable b. must have the same units as the variable doing the predicting c. usually is denoted by x d. is the independent variable The equation that describes how the dependent variable ( y) is related to the independent variable ( x) is called _____. a. the correlation model b. the regression model c. correlation analysis d. None of the answers is correct. The difference between the observed value of the dependent variable and the value predicted by using the estimated regression equation is called _____. a. a prediction interval b. the standard error c. a residual d. the variance Regression analysis is a statistical procedure for developing a mathematical equation that describes how _____. a. one independent and one or more dependent variables are related b. several independent and several dependent variables are related c. one dependent and one or more independent variables are related d. None of the answers is correct A procedure used for finding the equation of a straight line that provides the best approximation for the relationship between the independent and dependent variables is ______. a. the most squares method b. the least squares method c. correlation analysis d. the mean squares method
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