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Stat-503  : Linear Models and Regression Analysis

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Course Contents

Definitions and forms of linear models, Functionally related models, Mean related model, Model classification. Least squares and unbiased estimation, Best linear unbiased estimation, Multiple regression analysis, Various approaches of subset selection procedures, Heterosedasticity, Autocorrelation, Multicollinearity, Outliers Diagnostics. Non-Linear Models.

Course Synopsis

To enable students to handle qualitative and quantitative data of cross sectional type and to fit adequate model, to check their diagnostics and to decide remedial in case of violation of assumptions.

Course Learning Outcomes

The students will be able to have a deeper understanding of the linear regression model and its limitations. The students can familiarize how to diagnose and apply corrections to some problems with the generalized linear model found in real data. They can be able to understand generalizations of the linear model to binary and count data.


StatQuest: What is a statistical model? by StatQuest with Josh Starmer

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Video 1: Introduction to Simple Linear Regression by dataminingincae

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StatQuest: Linear Models Pt.1 - Linear Regression

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StatQuest: Fitting a line to data, aka least squares, aka linear regression.

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StatQuest: Linear Models Pt.1.5 - Multiple Regression by StatQuest with Josh Starmer

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Linear Regression and Multiple Regression by CodeEmporium

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Day 4: Multiple linear regression with matrices by mumfordbrainstats

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Multiple Linear Regression in Matrix Form by Steve L

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Video 5: Dummy Variables by dataminingincae

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Video 6: Variable Selection by dataminingincae

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Model Selection in Multiple Regression by OpenIntroOrg

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Subset Selection | Feature Selection | Stepwise Selection | Machine L by Big Eduearning

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Simple Linear Regression: Checking Assumptions with Residual Plots by jbstatistics

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Statistics 101: Nonlinear Regression, The Piecewise Model by Brandon Foltz

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Statistics 101: Nonlinear Regression, The Very Basics by Brandon Foltz

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POLYNOMIAL REGRESSION by SuperDataScience - Tableau and Data Visualisation

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What is Heteroskedasticity? by zedstatistics

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What is autocorrelation? Extensive video! by zedstatistics

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What is Multicollinearity? Extensive video + simulation! by zedstatistics

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Leverage and Influential Points in Simple Linear Regression by jbstatistics

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Book Title : Applied Linear Regression
Author : SANFORD WEISBERG
Edition : 4th
Publisher : John Wiley & sons, inc., Punlication
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Book Title : Applied Linear Statistical Models
Author : Michael H. Kutner, Christopher J. Nachtsheim, John Neter, William Li
Edition : 5th
Publisher : McGraw-Hill!Irwin
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Book Title : Handbook of Regression Analysis
Author : Samprit Chatterjee, Jeffrey S. Simonoff
Edition :
Publisher : John Wiley & sons, inc., Punlication


Book Title : Introduction to Linear Regression Analysis
Author : Montgomery, Peck, Vining
Edition : 5th
Publisher : John Wiley & sons, inc., Punlication






Title : Applied Linear Regression
Type : Reference Book

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Title : Applied Linear Statistical Models
Type : Reference Book

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Title : Handbook of Regression Analysis
Type : Reference Book

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Title : Introduction to Linear Regression Analysis
Type : Reference Book

View Introduction to Linear Regression Analysis

Title : Simple Linear Regression Introduction
Type : Presentation

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Title : Simple Linear Regression
Type : Presentation

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Title : Multiple Regression Analysis
Type : Presentation

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Title : Multiple Regression Analysis Example
Type : Presentation

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Title : Least Square
Type : Presentation

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Title : Functional Form of Regression
Type : Presentation

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Title : Introduction to Regression Analysis
Type : Presentation

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Title : Model selection
Type : Presentation

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Title : Variable Selection
Type : Presentation

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Title : Multicollinearity
Type : Presentation

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Title : Autocorrelation
Type : Presentation

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Title : hetroscedasticity
Type : Presentation

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Title : Linear Regression
Type : Other

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Title : Simple Linear Regression model
Type : Other

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Title : Multiple Regression Analysis
Type : Other

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Title : Multiple Linear Regression Model
Type : Other

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Title : Functional Form of Regression Models
Type : Other

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Title : Model selection
Type : Other

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Title : Automated Selection Procedure
Type : Other

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Title : Remedial Measures
Type : Other

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Title : Multicollinearity
Type : Other

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Title : Autocorrelation
Type : Other

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Title : hetroscedasticity
Type : Other

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Title : Non Linear Models
Type : Other

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