Question

13
After fitting a linear regression to time-series data, you find the residual plot to be non-linear
What is your conclusion?
(3 Points)
Non - Random plots are a consequence of the central limit theorem.
K-NN Regression might fit the data better.
Non-linear models might fit the data better.
Linear time series models suffice the data​

Answer 1

Answer:

Explanation:

Linear relationship: There exists a linear relationship between the independent variable, x, and the dependent variable, y.

Independence: The residuals are independent. ...

Homoscedasticity: The residuals have constant variance at every level of x.

Normality: The residuals of the model are normally distributed. PLZ MARK ME AS BRILLIANT