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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

Description:

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.

Linear Regression Concept and with R Video Series

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#Mathematics #Statistics & Probability #Linear Regression #Data Science #Data Analysis #Programming #Domain-Specific Languages (DSL) #R Programming