*plz answer quick* the correlation coefficient between two quantitative variables is approximately 0.6. what does the value of this correlation coefficient indicate about how well the model fits the data? answer choice's a. the model is not a good fit. b. the model is a good fit. c. the correlation coefficient is not within the correct range. d. no conclusion can be drawn regarding how well the model fits the data.

A.  

The model is not a good fit.

Step-by-step explanation:

The correlation coefficient is a measure of the degree of association between two quantitative variables , such as weight and height.

On the other hand, the quantity R-squared is an indicator of the predictive power of a model. It is an indicator of how well the model fits the data. R-squared is the coefficient of determination.

R-squared = the square of the correlation coefficient

                  = 0.6 * 0.6

                  = 0.36

Therefore, only 36% of the variations in the dependent variable can be explained by the model. More than 50% can thus not be explained by the model. The model is thus not a good fit.

easy math just plug in a and b

step-by-step explanation:

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