Respuesta :
Answer:
d. can be equal to the value of the coefficient of determination (r2).
True on the special case when r =1 we have that [tex] r^2 = 1[/tex]
Step-by-step explanation:
We need to remember that the correlation coefficient is a measure to analyze the goodness of fit for a model and is given by:
[tex]r=\frac{n(\sum xy)-(\sum x)(\sum y)}{\sqrt{[n\sum x^2 -(\sum x)^2][n\sum y^2 -(\sum y)^2]}}[/tex]
The determination coefficient is given by [tex] R= r^2[/tex]
Let's analyze one by one the possible options:
a. can never be equal to the value of the coefficient of determination (r2).
False if r = 1 then [tex] r^2 = 1[/tex]
b. is always larger than the value of the coefficient of determination (r2).
False not always if r= 1 we have that [tex] r^2 =1[/tex] and we don't satisfy the condition
c. is always smaller than the value of the coefficient of determination (r2).
False again if r =1 then we have [tex] r^2 = 1[/tex] and we don't satisfy the condition
d. can be equal to the value of the coefficient of determination (r2).
True on the special case when r =1 we have that [tex] r^2 = 1[/tex]
