T F 1. If a scatter diagram shows very little scatter about a straight line drawn through the plots, it indicates a rather weak relationship.

T F 4. There are two variables in correlation analysis referred to as the dependent and determination variables.

T F 5. Correlation analysis is a group of statistical techniques used to measure the strength of the relationship (correlation) between two variables.

T F 10. A correlation coefficient equal to –1 or +1 indicates perfect correlation.

T F 12. A coefficient of correlation, r, close to 0 (say, 0.08) shows that the relationship between two variables is quite weak.

T F 13. Correlation coefficients of –0.91 and +0.91 represent relationships between two variables that have equal strength but different directions.

T F 17. If the coefficient of correlation is –0.90, the coefficient of determination is –0.81.

T F 20. The coefficient of determination is the proportion of total variation in Y that is not explained by X.

T F 23. The standard error of estimate measures the accuracy of our prediction.

T F 27. A t test is used to test the significance of the coefficient of correlation.

T F 28. To test the significance of r, we use the standard normal z distribution.

T F 30. When testing the strength of the relationship between two variables, the alternate hypothesis is: H0: 0.

T F 37. The values of a and b in the regression equation are called the regression coefficients.

T F 46. A confidence interval can be determined for the mean value of Y for a given value of X.

T F 49. Explained variation equals total variation minus unexplained variation.

T F 50. In regression analysis, there is no difference in the width of a confidence interval and the width of a predictor interval.

T F 52. In the ANOVA table for regression, the total sum of squares is the sum of the treatment and error sum of squares.

T F 53. In the ANOVA table for regression, the total degrees of freedom is the sum the regression and error degrees of freedom.

T F 54. In a regression ANOVA table, the standard error of the estimate can be computed as the square root of the error mean square.

T F 55. In a regression ANOVA table, the coefficient of determination can be computed as the regression sum of squares divided by the total sum of squares.