Which of the following is a true statement? a) the correlation coefficient r is always greater than 1. b) the coefficient of determination can never assume negative values. c) the variable that is being predicted in regression analysis is the independent variable. d) a negative correlation indicates that as values of x decrease, values of y will decrease. e) if there is no correlation between the independent and dependent variables, then the value of the correlation coefficient must be -1. f) none of the above

f) None of the above.

Step-by-step explanation:

When we try to adjust a curve from a scatter plot to try and predict values of the dependent variable y given known values of the independent variable x.

The curve is a function y=f(x) which usually is a line, a logarithmic, parabola, power or exponential.

In order to choose which curve adjust the best, we compute a number r called correlation coefficient.

The closer r  is to -1 or +1, the better the curve adjust the scatter plot.

When r =0, we say there is no correlation between the points x and y

When -1<r<0 we say there is a negative correlation, this means that the values of y decrease as the values of x increase.

When 0<r<1 we say there is a positive correlation, this means that the values of y increase as the values of x increase.

When r =1 or r =-1, we say that there is a perfect correlation. It means that all of the points of the scatter plot lie on the curve.

So, from the possible choices of answer, f) None of the above is the right one.

idk lol

step-by-step explanation: