Lecture
Randomization tests: Understanding Experimental Results
Related lectures (35)
Protein Mass Spectrometry and Proteomics: Randomization Overview
Explores the significance of randomization in protein mass spectrometry and proteomics, highlighting its role in minimizing bias and ensuring research validity.
Experimental Design and Analysis
Covers the basics of experimental design and analysis, focusing on statistical techniques like ANOVA, regression, mediation, and moderation.
Confidence Intervals and T-Test
Explores confidence intervals, T-test, and hypothesis testing, including assumptions and critical regions.
Hypothesis Testing: T-Test Methodology
Explores hypothesis testing methodology using t-tests and the randomization test.
Hypothesis Testing: State of Nature
Explores hypothesis testing, emphasizing the state of nature and the importance of choosing the most powerful test.
Statistical Hypothesis Testing
Covers statistical hypothesis testing, confidence intervals, p-values, and significance levels in hypothesis testing.
Z-Test: Hypothesis Testing
Introduces hypothesis testing, focusing on the Z-test and critical regions.
Statistical Hypothesis Testing: Basics and Applications
Covers the basics of statistical hypothesis testing, p-values, confidence levels, and t-tests.
Bayesian Statistics: Hypothesis Testing and Estimation
Covers hypothesis testing, p-values, significance levels, and Bayesian estimation.
Design and Analysis of Experiments
Covers the design and analysis of experiments, focusing on statistics for experimenters.