Lecture 4 of 32Week 2
Simple Linear Regression (Part D)
Prof. Soumen Maity · IISER Pune
Credits and licence
- From
- Regression Analysis, IISER Pune (at NPTEL)
- Licence
- CC BY-NC-SA, as NPTEL states it. Non-commercial use only.
- Attribution
- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge. Coordinated by IIT Madras.
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All the lectures
- Simple Linear Regression(Part A)
- Simple Linear Regression (Part B)
- Simple Linear Regression (Part C)
- Simple Linear Regression (Part D)
- Simple Linear Regression (Part E)
- Multiple Linear Regression (Part A)
- Multiple Linear Regression (Part B)
- Multiple Linear Regression (Part C)
- Multiple Linear Regression (Part D)
- Selecting the BEST Regression Model (Part A)
- Selecting the BEST Regression Model (Part B)
- Selecting the BEST Regression Model (Part C)
- Selecting the BEST Regression Model (Part D)
- Multicollinearity (Part A)
- Multicollinearity (Part B)
- Multicollinearity (Part C)
- Model Adequacy Checking (Part A)
- Model Adequacy Checking (Part B)
- Model Adequacy Checking (Part C)
- Test for Influential Observations
- Transformation and Weighting to correct model inadequacies (Part A)
- Transformation and Weighting to correct model inadequacies (Part B)
- Transformation and Weighting to correct model inadequacies (Part C)
- Dummy Variables (Part A)
- Dummy Variables (Part B)
- Dummy Variables (Part C)
- Polynomial Regression Models (Part A)
- Polynomial Regression Models (Part B)
- Polynomial Regression Models (Part C)
- Generalized Linear Model (Part A)
- Generalized Linear Model (Part B)
- Non-Linear Estimation