Question

question number 5. which of the following is a true statement? the correlation coefficient r is always greater than 1. if there is no correlation between the independent and dependent variables, then the value of the correlation coefficient must be -1. a negative correlation indicates that as values of x increase, values of y will decrease. the variable that is being predicted in regression analysis is the independent variable. the coefficient of determination can assume negative values. none of the above

Explanation:

The correlation coefficient $r$ ranges from - 1 to 1. A negative correlation means that as one variable (e.g., $x$) increases, the other variable (e.g., $y$) decreases. The coefficient of determination $R^{2}$ (square of $r$) is non - negative. In regression, the variable being predicted is the dependent variable.

Answer:

A negative correlation indicates that as values of x increase, values of y will decrease.