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Hypothesis Testing and P-value Pitfalls

Wednesday, August 28, 2019, 7:00 PM


Hypothesis testing is the foundation of statistical inference procedures yet the meaning of the results (e.g., p-values and confidence intervals) often is not fully understood or appreciated by investigators potentially leading to a misinterpretation of the results. In this seminar, we will review the history and intent of inferential testing, discuss what Type I and II errors are, how they impact interpretation of results and are related to statistical power. We will examine current criticisms of the use and interpretations of results based on p-values and provide recommendations for addressing limitations of the classic null hypothesis significance testing framework. Participants in this seminar will gain a more in-depth understanding of the objectives and limitations of classical inferential testing which will allow them to more critically examine and interpret statistical analysis results. Learning objectives: Understand how to interpret p-values and confidence intervals Be able to formulate research hypotheses for a statistical test Appreciate Type I and II errors and their relation to power analysis and sample size calculations

Tickets: https://www.eventbrite.com/e/hypothesis-testing-and-p-value-pitfalls-tickets-62258133754?aff=aff0eventful

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Venue

451 Health Sciences Drive , Room 4202
Davis, CA

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