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Regression Analysis

Prof. Soumen Maity · IISER Pune

Start with lecture 1 At NPTEL

About

Regression analysis is one of the most powerful methods in statistics for determining the relationships between variables and using these relationships to forecast future observations. The foundation of regression analysis is very helpful for any kind of modelling exercises. Regression models are used to predict and forecast future outcomes. Its popularity in finance is very high; it is also very popular in other disciplines like life and biological sciences, management, engineering, etc. In this online course, you will learn how to derive simple and multiple linear regression models, learn what assumptions underline the models, learn how to test whether your data satisfy those assumptions and what can be done when those assumptions are not met, and develop strategies for building best models. We will also learn how to create dummy variables and interpret their effects in multiple regression analysis; to build polynomial regression models and generalized linear models.

Intended audience: B.Sc, M.Sc, B.Tech, M.Tech

Prerequisites: Probability and Statistics

Lectures

Week 1

  1. Simple Linear Regression(Part A) YouTube
  2. Simple Linear Regression (Part B) YouTube
  3. Simple Linear Regression (Part C) YouTube

Week 2

  1. Simple Linear Regression (Part D) YouTube
  2. Simple Linear Regression (Part E) YouTube
  3. Multiple Linear Regression (Part A) YouTube

Week 3

  1. Multiple Linear Regression (Part B) YouTube
  2. Multiple Linear Regression (Part C) YouTube
  3. Multiple Linear Regression (Part D) YouTube

Week 4

  1. Selecting the BEST Regression Model (Part A) YouTube
  2. Selecting the BEST Regression Model (Part B) YouTube

Week 5

  1. Selecting the BEST Regression Model (Part C) YouTube
  2. Selecting the BEST Regression Model (Part D) YouTube

Week 6

  1. Multicollinearity (Part A) YouTube
  2. Multicollinearity (Part B) YouTube
  3. Multicollinearity (Part C) YouTube

Week 7

  1. Model Adequacy Checking (Part A) YouTube
  2. Model Adequacy Checking (Part B) YouTube
  3. Model Adequacy Checking (Part C) YouTube

Week 8

  1. Test for Influential Observations YouTube
  2. Transformation and Weighting to correct model inadequacies (Part A) YouTube

Week 9

  1. Transformation and Weighting to correct model inadequacies (Part B) YouTube
  2. Transformation and Weighting to correct model inadequacies (Part C) YouTube

Week 10

  1. Dummy Variables (Part A) YouTube
  2. Dummy Variables (Part B) YouTube
  3. Dummy Variables (Part C) YouTube

Week 11

  1. Polynomial Regression Models (Part A) YouTube
  2. Polynomial Regression Models (Part B) YouTube
  3. Polynomial Regression Models (Part C) YouTube

Week 12

  1. Generalized Linear Model (Part A) YouTube
  2. Generalized Linear Model (Part B) YouTube
  3. Non-Linear Estimation YouTube

Syllabus and materials

At NPTEL, as the course publishes them.

Credits and licence

Institution
IISER Pune
Department
Mathematics
Teacher
Prof. Soumen Maity
Level
Undergraduate
Language
English
Subjects
Mathematics
Source
NPTEL
Licence
CC BY-NC-SA, as NPTEL states it. Non-commercial use only. NPTEL's terms
Attribution
NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge. Coordinated by IIT Madras.
Who can watch
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