Model selection with AIC and AICc

Statistics 101: Multiple Regression, AIC, AICc, and BIC Basics

Forward and backward selection and best subset selection

PCA : the basics - explained super simple

Time Series Model Selection (AIC & BIC) : Time Series Talk

AIC intro

AnalyticsX: AIC and BIC

Uji ADF dan kriteria AIC/BIC

Linear mixed effects models - random slopes and interactions | R and SPSS

PERMANOVA and permutation tests - explained

Assumptions in Linear Regression - explained | residual analysis

Lesson47 Akaike Information Criterion

MLE vs OLS | Maximum likelihood vs least squares in linear regression

Lasso regression - explained

Model selection with AICs

Video 2: Confidence Intervals

Logistic regression : the basics - simply explained

Logistic regression : how to use it as a classifier

One-way ANOVA: the basics

Teach me STATISTICS in half an hour! Seriously.

Building and Comparing Mixed Models in R: ICC, Bayes Factor, and Variance Explained