Multiple Testing Problem

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Statistical Theory: Inference and Optimality

Explores constructing confidence regions, inverting hypothesis tests, and the pivotal method, emphasizing the importance of likelihood methods in statistical inference.

Principal Component Analysis: Understanding Data Structure

Explores Principal Component Analysis, dimensionality reduction, data quality assessment, and error rate control.

Strategy Selection

Explores strategy selection challenges, performance evaluation, and statistical testing in finance, emphasizing the importance of strategy portfolios.

Genome-wide Association Studies: Statistical Analysis

Explains the statistical analysis of Genome-wide Association Studies and the importance of adjusting for multiple testing.

Analysis of Variance: Principles and Applications

Explores the principles and applications of Analysis of Variance (ANOVA), including test hypotheses, models, assumptions, and post-hoc tests.

Hypothesis Testing in Statistics

Explores hypothesis testing, significance levels, errors, GWAS, optimal testing, and point estimation in statistics.

Optimal Tests for Simple Hypotheses

Discusses optimal tests for simple hypotheses and the significance of standardized distance in hypothesis testing.

Hypothesis Testing and Confidence Intervals: An Overview

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

Statistics & Experimental Design

Explores conditional probability, Framingham studies, effect size, t-test, and sampling error in statistics.

Statistical Hypothesis Testing: Unilateral and Bilateral Pairs

Explores unilateral and bilateral pairs in statistical hypothesis testing, covering critical values, test statistics, and p-values.