Question

Jayne collects data during several experiments and tries to see if a linear model would be a good fit for the data. She

finds the correlation coefficient for each data set.
Which experiment's correlation coefficient indicates that a linear model is not a good fit for the data?
(picture included)

Answer 1

Answer

R ~ 0.03

Explanation

For Pearson’s Product Correlation Coefficient, an R value can only be in the range of -1 to +1.

-1 = perfect negative correlation
+1 = Perfect positive correlation

Values in between and approaching 0 means there is weak to no correlation.