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R Programming Complete Tutorial

Multiple Linear Regression

Multiple Linear Regression is an extension of simple linear Regression used to predict a target variable (y) on the basis of multiple predictor variables (x). The model remains linear as the output is a linear combination of the input variables. Fast and simple to model, and especially useful when the relationship is not extremely complex, and we don't have a lot of data to model. Linear Regression is very sensitive to outliers.

Example:

  • We have a data set containing the impact of three advertising media (youtube, facebook, and newspaper) on sales.

  • From these predictors, we can predict our sales.

  • This 3d graph represents the relationship between predictors (youtube and facebook ) and the target variable.

Diagram output:

This is a three-dimensional representation of facebook and youtube data with respect to sales.