Statistics Essentials: The t-testIntroduces the t-test for assessing categorical effects on quantitative outcomes, covering hypothesis testing, assumptions, and alternative tests.
Detection & EstimationCovers the fundamentals of detection and estimation theory, focusing on mean-squared error and hypothesis testing.
Estimation CriteriaCovers criteria for estimating parameters, emphasizing the importance of consistency, bias, variance, and efficiency of estimators.
Central Tendency and DispersionExplores replicates, visualization methods, central tendency measures, outliers, dispersion, averages, residuals, and unbiased estimators.
