Module Introduction- Logistic Regression

Welcome to the module on ‘**Logistic Regression**’. In the last module on linear regression, you learnt how a linear regression model can be used to make predictions for continuous variables.

## In this module

Now, in this module, you will learn logistic regression, which is a **classification model**, i.e. it will help you make predictions in cases where the output is a categorical variable.

Since logistic regression is the most easily interpretable of all classification models, it is very commonly used in various industries such as banking, healthcare, etc.

## Prerequisites

You’ll need to brush up on basic maths related to exponentials and logarithms before you begin this session. You can brush up on these topics using the links given below.

You can also solve the practice questions provided in the Resources section.

#### Guidelines for in-module questions

The in-video and in-content questions for this module are not graded. Note that graded questions are given on a separate page labelled ‘Graded Questions’ at the end of this session. The graded questions in this session will adhere to the following guidelines.

First Attempt Marks | Second Attempt Marks | |

Questions with 2 Attempts | 10 | 5 |

Questions with 1 Attempt | 10 | 0 |