Question

Which characteristic of a data set makes a linear regression model unreasonable?

Answer 1

A linear regression model would be unreasonable for data that follows

a) quadratic model

b) cubic model

c) data that can be modeled by polynomials of higher degrees

d) random/scattered data

e) all other nonlinear pattern.

Answer 2

Answer:

A correlation coefficient close to 0 makes a linear regression model unreasonable.

Because If the correlation between the two variable is close to zero, we can not expect one variable explaining the variation in other variable. For a linear regression model to be reasonable, the most important thing is to see whether the two variables are correlated. If there is correlation between the two variable, we can think of regression analysis and if there is no correlation between the two variable, it does not make sense to apply regression analysis.

Therefore, if the correlation coefficient is close to zero, the linear regression model would be unreasonable.