IIT Madras LSM Lectures: Linear Statistical Models
BSMA301247 lectures12 weeks
Weeks
- Week 14 lecturesBasic calculations and introduction to r · Introduction to data and basic visualization techniques · Data visualization using ggplot2 · Data Visualization using ggplot()-geoms
- Week 24 lecturesSampling distributions · More on sampling distribution · Introduction to modeling · Technique to find the best fit of linear model
- Week 33 lecturesFundamentals of linear models and estimation problem · Theory of linear models · Problem of parameter estimation
- Week 44 lecturesDifferent classifications of linear models · Normal equations and existence of least square estimates · Theorem on least square estimates · Fundamentals of matrices
- Week 54 lecturesEstimating the coefficients of linear model · Interval estimate and hypothesis testing for coefficients of linear model · Assess the linear model by using rse and r square · Computation of least square estimates in r
- Week 64 lecturesIntroduction to blue and gauss-markov theorem · Proof of gauss-markov theorem · Variance of blue and linear zero estimators · Assumption of normality
- Week 74 lecturesSignificance of gauss-markov theorem · 3d plot of multiple regression in r · Linear regression with real data in r · Simulation for sample distribution of least square estimators
- Week 85 lecturesIntroduction to hypothesis testing · Basic idea to test simple linear regression · Testing of linear hypothesis · Proof of second fundamental theorem of least squares · Introduction to anova table
- Week 94 lecturesTesting for one way classification model · Testing of model in general case · Least square estimates of two way classification model · Testing of two way classification model
- Week 104 lecturesT-testing for SLM in R · T-testing for multiple linear regression in R · One way anova in R · Anova by using basic code in r
- Week 113 lecturesIntro to random effect models · One way random effect model · Two way random effect model & mixed effect model
- Week 124 lecturesFixed effect model in r · Random effect model in r · Difference between fixed and random effect model · More Examples on Random Effect model and Fixed Effect Model