The interpretation of the sample correlation coefficient is r^2 = 0.835 83.5% of

Question

The interpretation of the sample correlation coefficient is r^2 = 0.835 83.5% of the total variability in GPAs can be explained by the variability in the GMAT Scores total variability in GPAs can be explained by the variability in the GMAT r = 0.914 91.4% of the Scores r = .914 there is a strong positive linear relationship between GPA and GMAT scores. r^2 = .835 there is a strong positive linear relationship between GPA and GMAT scores. Does the following scatter diagram indicate that there is a strong linear relationship between and GMAT scores? Yes. Because the scatter diagram has GMAT scores between 500 and 800. Yes. All the points are moving in an upward manner indicating a line should be fit through the data. Yes. All the points are clustered very closely to the line. This indicates that the GMAT scores strongly depend on the GPA. Yes. All the points are clustered very closely to the line. This indicates that the GPA strongly depends on the GMAT score.

Explanation / Answer

51) option A and C is correct ; as r2 shows variabilty in regression and r shows strength of relationship

52)option D is correct.

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