Hypothesis Testing in Statistics

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Related lectures (31)

Genome-wide Association Studies: Statistical Analysis

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

Hypothesis Testing in Statistics

Explores hypothesis testing in statistics, focusing on decision-making based on sample data and controlling error probabilities.

Statistical Theory: Cramér-Rao Bound & Hypothesis Testing

Explores the Cramér-Rao bound, hypothesis testing, and optimality in statistical theory.

Chi-Square Test: Independence Hypothesis

Explains the Chi-Square test for independence hypothesis and its practical applications.

Hypothesis Testing and Confidence Intervals: An Overview

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

Statistical Hypothesis Testing: Inference and Interpretation

Explores statistical hypothesis testing, including constructing confidence intervals, interpreting p-values, and making decisions based on significance levels.

Likelihood Ratio Test: Neyman-Pearson Lemma

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

Strategy Selection

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

Likelihood Ratio Test: Hypothesis Testing

Covers the Likelihood Ratio Test and hypothesis testing methods using Maximum Likelihood Estimators.

Describing Data: Statistics and Hypothesis Testing

Covers descriptive statistics, hypothesis testing, and correlation analysis with various probability distributions and robust statistics.

Statistics Essentials: The t-test

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

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