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Regression Analysis. Instructor: Dr. Soumen Maity, Department of Mathematics, IIT Kharagpur.

FREE
This course includes
Hours of videos

1111 years

Units & Quizzes

40

Unlimited Lifetime access
Access on mobile app
Certificate of Completion

This course discusses topics in regression analysis: simple linear regression, multiple linear regression, selecting the best regression model, multicollinearity, model adequacy checking, test for influential observations, transformations and weighting to correct model inadequacies, dummy variables, polynomial regression models, generalized linear models, nonlinear estimation, regression models with autocorrelated errors, measurement errors and calibration problem. (from nptel.ac.in)

Course Currilcum

    • Lecture 01 – Course Introduction, Simple Linear Regression Unlimited
    • Lecture 02 – Useful Properties of Least Squares Fit, Statistical Properties of Least Squares Estimators Unlimited
    • Lecture 03 – Estimation of σ2, Confidence Intervals and Tests for β0 and β1 Unlimited
    • Lecture 04 – Analysis of Variance (ANOVA), Coefficient of Determination Unlimited
    • Lecture 05 – Confidence Interval of β1, Interval Estimation of the Mean Response Unlimited
    • Lecture 06 – Estimation of Model Parameters, Properties of Least Squares Estimators Unlimited
    • Lecture 07 – Hypothesis Testing in Multiple Linear Regression Unlimited
    • Lecture 08 – Example on Multiple Linear Regression Unlimited
    • Lecture 09 – Extra Sum of Squares Method, Confidence Intervals in Multiple Regression Unlimited
    • Lecture 10 – All Possible Regression Approach Unlimited
    • Lecture 11 – All Possible Regression Approach (cont.) Unlimited
    • Lecture 12 – Sequential Selection: Backward Elimination, Forward Selection Unlimited
    • Lecture 13 – Sequential Selection: Forward Selection (cont.), Stepwise Selection Unlimited
    • Lecture 14 – Multicollinearity Unlimited
    • Lecture 15 – Effects of Multicollinearity (cont.), Multicollinearity Diagnostics Unlimited
    • Lecture 16 – Multicollinearity Diagnostics (cont.), Methods for Dealing with Multicollinearity Unlimited
    • Lecture 17 – Residuals: Regular Residuals, Standardized Residuals, Studentized Residuals Unlimited
    • Lecture 18 – PRESS Residuals, Residual Plots Unlimited
    • Lecture 19 – The Plot of Residual against the Regressor, Partial Residual Plot Unlimited
    • Lecture 20 – Test for Influential Observations Unlimited
    • Lecture 21 – Variance-stabilizing Transformations, Transformations to Linearize the Model Unlimited
    • Lecture 22 – Generalized and Weighted Least Square Unlimited
    • Lecture 23 – Analytic Models to Select a Transformation Unlimited
    • Lecture 24 – Dummy Variables to Separate Blocks of Data Unlimited
    • Lecture 25 – Interaction Terms Involving Dummy Variables Unlimited
    • Lecture 26 – Three Sets of Data and Straight Line Models Unlimited
    • Lecture 27 – Polynomial Models in One Variable and Orthogonal Polynomials Unlimited
    • Lecture 28 – Piecewise Polynomial Fitting Unlimited
    • Lecture 29 – Polynomial Models in Two or More Variables Unlimited
    • Lecture 30 – The Exponential Family of Distributions, Fitting Generalized Linear Models Unlimited
    • Lecture 31 – Generalized Linear Models (cont.) Unlimited
    • Lecture 32 – Nonlinear Estimation: Nonlinear Models, Least Square in Nonlinear Case Unlimited
    • Lecture 33 – Source and Effect of Autocorrelation, Detecting the Presence of Autocorrelation Unlimited
    • Lecture 34 – Parameter Estimation in the Presence of Autocorrelation Model Unlimited
    • Lecture 35 – Measurement Errors and Calibration Problem Unlimited
    • Lecture 36 – Solving Problems from Simple Linear Regression Model Unlimited
    • Lecture 37 – Solving Problems from Linear Regression Models Unlimited
    • Lecture 38 – Solving Problems Unlimited
    • Lecture 39 – Solving Problems: Coefficient of Determination, Autocorrelated Errors Unlimited
    • Lecture 40 – Nonlinear Estimation, Generalized Linear Models, Dummy Variables Unlimited