In this session
- We identified the presence of non-linearity in our data for both simple and multiple linear regression. For this, we use residual plots.
- The ways in which we can handle non-linearity are
- Polynomial Regression
- Data Transformation
- Non-linear Regression
- Polynomial regression is a very simple way to directly extend the linear model to accommodate nonlinear relationships.
- We also saw how data transformation helps us to obtain a good fit of model on data.
- In the last segment, we discussed some of the problems which may observe when we fit a linear regression model to a particular data set.
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