Covers binary classification, hypothesis testing, likelihood ratio tests, and decision rules.
Introduces descriptive statistics, uncertainty quantification, and variable relationships, emphasizing the importance of statistical interpretation and critical analysis.
Explores hypothesis testing in statistics, focusing on decision-making based on sample data and controlling error probabilities.
Covers probability, random variables, expectation, GLMs, hypothesis testing, and Bayesian statistics with practical examples.
Covers t-tests, p-values calculation, and comparison of coefficients.
