Lecture
Hypothesis Testing in Statistics
Description
This lecture by the instructor covers hypothesis testing in statistics, focusing on the Pearson statistic and its application in checking the fit between data and probabilities. It delves into significance levels, type 1 and type 2 errors, and the practical implications of statistical significance. The lecture also includes a detailed example of genome-wide association studies (GWAS) and the importance of adjusting for multiple testing. Additionally, it discusses the Neyman-Pearson lemma for optimal testing and the concept of point estimation in statistical modeling.
Instructors (2)
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