IKH

Session Summary

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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