ANOVA & Moderation

Related lectures (31)

Page 3 of 4

Introduces simple and multiple normal linear regression, and maximum likelihood estimation with practical examples.

Discusses estimation methods in probability and statistics, focusing on maximum likelihood estimation and confidence intervals.

Covers linear regression coefficients, confidence intervals, and R's calculation methods.

Introduces the Binomial distribution in R with examples of n coin tosses.

Explores ANOVA, factorial experiments, and model evaluation techniques.

Covers the basics of experimental design and analysis, focusing on statistical techniques like ANOVA, regression, mediation, and moderation.

Explores the academic conference rebuttal process, emphasizing data analysis for paper acceptance, machine learning, and statistical tests.

Introduces linear models for supervised learning, covering overfitting, regularization, and kernels, with applications in machine learning tasks.

Explores logistic regression for predicting vegetation proportions in the Amazon region through remote sensing data analysis.

Explores model selection criteria like AIC, BIC, and Cp in statistics for data science.