Dive into a comprehensive video series on linear regression concepts and their implementation in R programming. Explore simple and multiple linear regression, covering model fitting, coefficient interpretation, assumption checking, and handling non-linearity. Learn about polynomial regression, categorical variables, dummy coding, and interaction effects. Master techniques for variable selection using partial F-tests and gain a deep understanding of R-squared. Through alternating theoretical explanations and practical R tutorials, develop a strong foundation in linear regression analysis for statistical modeling and data science applications.
Overview
Syllabus
Simple Linear Regression Concept | Statistics Tutorial #32 | MarinStatsLectures.
Simple Linear Regression in R | R Tutorial 5.1 | MarinStatsLectures.
Checking Linear Regression Assumptions in R | R Tutorial 5.2 | MarinStatsLectures.
Linearity and Nonlinearity in Linear Regression | Statistics Tutorial #33 | MarinStatsLectures.
Multiple Linear Regression in R | R Tutorial 5.3 | MarinStatsLectures.
Changing Numeric Variable to Categorical in R | R Tutorial 5.4 | MarinStatsLectures.
Dummy Variables or Indicator Variables in R | R Tutorial 5.5 | MarinStatsLectures.
Change Reference (Baseline) Category in Regression with R | R Tutorial 5.6 | MarinStatsLectures.
R Squared or Coefficient of Determination | Statistics Tutorial | MarinStatsLectures.
Including Variables/ Factors in Regression with R, Part I | R Tutorial 5.7 | MarinStatsLectures.
Including Variables/ Factors in Regression with R, Part II | R Tutorial 5.8 | MarinStatsLectures.
Multiple Linear Regression with Interaction in R | R Tutorial 5.9 | MarinStatsLectures.
Interpreting Interaction in Linear Regression with R | R Tutorial 5.10 | MarinStatsLectures.
Partial F-Test for Variable Selection in Linear Regression | R Tutorial 5.11| MarinStatsLectures.
Polynomial Regression in R | R Tutorial 5.12 | MarinStatsLectures.
Simple Linear Regression | Statistics for Applied Epidemiology | Tutorial 1.
Multiple Linear Regression | Statistics for Applied Epidemiology | Tutorial 2.
Multiple Linear Regression II | Statistics for Applied Epidemiology | Tutorial 3.
Multiple Linear Regression III | Statistics for Applied Epidemiology | Tutorial 4.
Taught by
MarinStatsLectures-R Programming & Statistics
