Lectures related to Hotelling's T-squared distribution

Explores confidence intervals, T-test, and hypothesis testing, including assumptions and critical regions.

Explains the two-sample t-test for comparing means of independent samples, including hypothesis testing steps and test statistic calculation.

Statistics Essentials: The t-test

Introduces the t-test for assessing categorical effects on quantitative outcomes, covering hypothesis testing, assumptions, and alternative tests.

Statistical Modeling: Estimation and Hypothesis Testing

Covers statistical modeling, estimation, CLT, confidence intervals, and hypothesis testing steps with practical examples.

Continuous Random Variables: Distributions and Expectation

Explores various continuous probability distributions and expectation of random variables.

Multivariate Statistics: Wishart and Hotelling T²

Explores the Wishart distribution, properties of Wishart matrices, and the Hotelling T² distribution, including the two-sample Hotelling T² statistic.

Introduction to t tests

Covers the basics of t tests, including hypothesis testing, significance levels, P-values, Z-tests, and the t distribution.

Sampling Theory: Statistics for Mathematicians

Covers the theory of sampling, focusing on statistics for mathematicians.

T-tests and Empirical Tests

Explores t-tests, z-tests, and empirical tests for sample comparison and hypothesis testing.

Estimators and Confidence Intervals

Explores bias, variance, unbiased estimators, and confidence intervals in statistical estimation.

DOE Qualitative factors: IV

Explores qualitative factors in Design of Experiments, including statistical tests and error types.

Statistical Hypothesis Testing: Basics and Applications

Covers the basics of statistical hypothesis testing, p-values, confidence levels, and t-tests.

Testing: t-tests

Covers t-tests, p-values calculation, and comparison of coefficients.

Statistical Tests: Independence and Homogeneity

Explores statistical tests for independence and homogeneity, including chi-square tests and Fisher's exact test, with practical examples and applications.

Hypothesis Testing: T-Test and Chi-Square Test

Explains hypothesis testing using T-test and Chi-square test to compare means and assess independence of variables.

Copulas and Extreme Values

Explores copulas for measuring dependence strength in distributions and transforming variables to unit Fréchet margins.

Randomization tests: Understanding Experimental Results

Explores randomization tests as an alternative to t-tests for experimental analysis, using fake data to assess treatment effectiveness.

Probability Distributions: Central Limit Theorem and Applications

Discusses probability distributions and the Central Limit Theorem, emphasizing their importance in data science and statistical analysis.

Heavy-Tailed Distributions

Explores heavy-tailed distributions, the Hill estimator, convergence to Gaussian, and distribution comparison.

Copulas and Margins: Extremal Dependence in Statistics

Delves into copulas, margins, and extremal dependence in statistics, covering topics like logistic copulas and Kendall's tau.