Answer:
The correlation coefficient is 0.60.
Step-by-step explanation:
<em>R</em>-squared is a statistical quantity that measures, just how near the values are to the fitted regression line. It is also known as the coefficient-of-determination.
The coefficient of determination <em>R</em>² specifies the percentage of the variance in the dependent variable (<em>Y</em>) that is forecasted or explained by linear regression and the forecaster variable (<em>X</em>, also recognized as the independent-variable).
The coefficient of determination <em>R</em>² can be computed by the formula,
The coefficient of determination is the square of the correlation coefficient.
The restaurant manager wanted to estimate the monthly sales for the restaurant from monthly advertising expenses.
Here,
<em>Y</em> = monthly sales for the restaurant
<em>X</em> = monthly advertising expenses
It is provided that, 36% of the variation in monthly sales could be explained by monthly advertising expenses.
That is, the value of <em>R</em>² is 0.36.
Compute the correlation coefficient value between <em>X</em> and <em>Y</em> as follows:
Now the values of monthly sales and monthly advertising expenses can never be negative.
So, the correlation between the two variables can never be negative either.
Thus, the correlation coefficient is 0.60.