# SOLUTION: T F 1. One of the objectives of simple linear regression is to predict the value of the independent variable X as a linear function of the dependent variable Y. T F 2. Regressio

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 Question 139046: T F 1. One of the objectives of simple linear regression is to predict the value of the independent variable X as a linear function of the dependent variable Y. T F 2. Regression analysis is limited to establishing a relationship between two variables, X and Y. T F 3. If a deterministic relationship exists between two variables, x and y, any value of x that is selected will determine a unique value of y. T F 4. When trying to uncover relationships between variables, the recommended practice is to construct a scatter plot first before conducting a statistical analysis. T F 10. Whenever regression analysis is used to predict values of Y that are within the range of the X data, the process is known as interpolation. T F 11. Extrapolation is most advisable if it is difficult to predict what the data relationship actually is beyond the range of the existing observations. T F 12. Residuals can be computed by taking the difference between observed and predicted values of Y and squaring them to eliminate negative numbers. T F 13. The sum of the residuals that surround a regression line will always be greater than or equal to zero. T F 14. The stronger the relationship between X and Y, the closer the plotted points will be to the regression line. T F 15. If two variables are highly correlated, the correlation coefficient will be at or near zero. T F 16. The power of regression analysis is best illustrated by the fact that the presence of outliers has practically no impact on the values of the coefficients or their standard deviations. Please indicate why the answer if FALSE> Thanks. Answer by stanbon(57361)   (Show Source): You can put this solution on YOUR website!T F 1. One of the objectives of simple linear regression is to predict the value of the independent variable X as a linear function of the dependent variable Y. False: X is the independent; Y is the dependent variable ------------------------------------- T F 2. Regression analysis is limited to establishing a relationship between two variables, X and Y. False: It may be used to measure linear relationships between more that one independent variable and the dependent variable. ----------------------- T F 3. If a deterministic relationship exists between two variables, x and y, any value of x that is selected will determine a unique value of y. True ------------------- T F 4. When trying to uncover relationships between variables, the recommended practice is to construct a scatter plot first before conducting a statistical analysis. True --------------------- T F 10. Whenever regression analysis is used to predict values of Y that are within the range of the X data, the process is known as interpolation. ? It might be; check your textbook. ----------------------- T F 11. Extrapolation is most advisable if it is difficult to predict what the data relationship actually is beyond the range of the existing observations. It might be. ------------------- T F 12. Residuals can be computed by taking the difference between observed and predicted values of Y and squaring them to eliminate negative numbers. False: Residuals are the difference between observed value and expected value for a particular value of "x". ------------------------------- T F 13. The sum of the residuals that surround a regression line will always be greater than or equal to zero. False ------------------- T F 14. The stronger the relationship between X and Y, the closer the plotted points will be to the regression line. True ----------------- T F 15. If two variables are highly correlated, the correlation coefficient will be at or near zero. False --------------------------- T F 16. The power of regression analysis is best illustrated by the fact that the presence of outliers has practically no impact on the values of the coefficients or their standard deviations. Could be. --------------------------- Please indicate why the answer if FALSE> Thanks. ============================================= Cheers, Stan H.