Suppose that we have N independent variables (X1, X2, Xn) and dependent variable is Y. Now Imagine that you are applying linear regression by fitting the best fit line using least square error on this data. You found that correlation coefficient for one of its variable(Say X1) with Y is -0.95. Which of the following is true for X1?

The correct answer is: B. relation between the x1 and y is strong.

A correlation coefficient of -0.95 is a very strong negative correlation. This means that as X1 increases, Y decreases. The closer the correlation coefficient is to -1, the stronger the negative correlation.

A correlation coefficient of 0 indicates no correlation. This means that there is no linear relationship between X1 and Y.

A correlation coefficient of 1 indicates a perfect positive correlation. This means that as X1 increases, Y also increases.

A correlation coefficient of -1 indicates a perfect negative correlation. This means that as X1 increases, Y decreases.

Please let me know if you have any other questions.