Applied Statistics for Translational Researchers Seminar Series: Hypothesis Testing and P-value Pitfalls
Registration link for this event live until August 28, 2019.
Speaker: Sandra Taylor, Ph.D.
Hypothesis testing is the foundation of statistical inference procedures. Yet the meaning of the results (e.g., p-values and confidence intervals) is often 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, and explore 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.
• Be able to formulate research hypotheses for a statistical test
• Understand p-values and confidence intervals
• Appreciate Type I and II errors and their relation to power analysis and sample size calculations
Registration preferred but not required. Registration link for this event live until August 28, 2019.
1 Shields Avenue
Davis, CA 95616