Model Selection in StatisticsExplores model selection in statistics, discussing principles, probabilistic models, characteristics evaluation, and data visualization methods.
Mean-Square-Error InferenceCovers the concept of mean-square-error inference and optimal estimators for inference problems using different design criteria.
Statistics Essentials: The t-testIntroduces the t-test for assessing categorical effects on quantitative outcomes, covering hypothesis testing, assumptions, and alternative tests.
Linear Regression BasicsCovers the basics of linear regression in machine learning, including model training, loss functions, and evaluation metrics.