American Statistical Association
New York City
Metropolitan Area Chapter
Virtual Refresher Short Course
Statistical Inference: History, Principles, and Developments

Friday, April 14, 2023
3:00 - 5:00 PM

The New York Metro Area Chapter of the American Statistical Association

Is Pleased to Invite You to a Virtual Refresher Short Course

Statistical Inference: History, Principles, and Developments


Kelly H. Zou


This presentation reviews several fundamental and important concepts concerning statistical inference, which is an extremely broad, if not all encompassing, topic. First, a historical perspective of statistical inference is provided by summarizing the developments over the last 200 years (e.g., the chi-square test constructed by Pearson and the likelihood-based statistical foundation established by Fisher). Both frequentist and Bayesian approaches are presented. Specifically, classical concepts reviewed include likelihood functions, exponential family, confidence intervals and regions, hypothesis tests, exact inference, large sample theory, and Bayesian methods. Advanced methods developed by the speaker include classification accuracy using a receiver operating characteristic analysis, monotone transformation theory, and statistical validation of predictive modeling.

This refresher course is suitable for researchers in statistics and other closely related fields. Practicing statisticians in academia, industry, and government may benefit from a review of such important and yet frequently overlooked topics. In his monograph entitled "Principles of Statistical Inference," which may serve as an important reference when reviewing these topics, Professor D.R. Cox wrote that "the object is to provide ideas and methods for the critical analysis and, as far as feasible, the interpretation of empirical data arising from a single experiment or observational study or from a collection of broadly similar studies bearing on a common target."

Key Words

Statistical Inference; Confidence Interval and Region; Maximum Likelihood Estimation; Hypothesis Tests; Transformation; Bayesian methods.

Instructor Biography

Kelly H. Zou, Ph.D., PStat® is Head of Global Medical Analytics and Real World Evidence, Viatris Inc. She is an elected Fellow of the American Statistical Association and an Accredited Professional Statistician. Previously at Pfizer Inc, she was Vice President and Head of Medical Analytics & Insights; Senior Director of Real World Evidence, Group Lead of Methods & Algorithms and Analytic Science Lead; Senior Director of Statistics. She was Associate Professor of Radiology at Harvard Medical School, as well as Director of Biostatistics at its affiliated teaching hospitals. She was Associate Director of Rates at Barclays Capital. She received both MA and PhD degrees in Statistics from the University of Rochester. She completed her Postdoctoral Fellowship at Harvard. Her research interests include health policy, real world evidence, signal detection, and artificial intelligence, with over 150 professional articles and 5 books. She was featured as an Outstanding Woman in Data Analytics by Forbes, an Inspirational Women in Statistics & Data Science by Wiley, and an Accomplished Woman in Statistics and Data Science by the American Statistical Association. She was the winner of the Chief Data and Analytics Officers' Forum's Future Thinking Award and Reuters Events Pharma USA's Most Valuable Data & Insights Initiative Team Award.

Presentation Slides

Date and Time
Friday, April 14, 2023
3:00 - 5:00 P.M. (US ET)

Virtual via Zoom

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