Can you guys check these for me

#1
Shade answers to T/F questions and type letter answer to multiple choice questions next to problem number. Chapters 13 & 14 included.
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.