Hotelling's T-squared distribution

Related lectures (29)

Page 3 of 3

Covers the analysis of heavy-tailed price returns and clustered volatility in financial data.

Introduces continuous random variables and their probability distributions, emphasizing their applications in statistics and data science.

Covers hypothesis testing, confidence intervals, and their applications in statistics.

Provides an overview of hypothesis testing and confidence intervals in statistics, including practical examples and key concepts.

Covers statistical design of experiments, focusing on minimizing costs and maximizing accuracy.

Explores likelihood ratio tests and the Neyman-Pearson Lemma for statistical hypothesis testing.

Covers risk measures used for determining risk capital and capital adequacy.

Covers statistics, experimental design, errors, distributions, implications of sample size, and null results.

Explores maximum likelihood estimation and multivariate hypothesis testing, including challenges and strategies for testing multiple hypotheses.