Andrew Zieffler

Academic. Data lover. Statistics enthusiast.

What to do about p-values?

In March, the ASA published a special issue of The American Statistician (TAS) related to statistical inference in the 21st century. In the initial article, Moving to a World Beyond “p < 0.05”, Wassersein, Schirm, and Lazar (2019) write for the ASA saying, “The ASA Statement on P-Values and Statistical Significance stopped just short of recommending that declarations of “statistical significance” be abandoned. We take that step here. We conclude, based on our review of the articles in this special issue and the broader literature, that it is time to stop using the term “statistically significant” entirely.

USCOTS 2019

Last week I attended the United States Conference on Teaching Statistics. The biennial conference, which took place at Penn State, attracts statistics educators and statistics education researchers from across the world. It was a fantastic conference with keynotes from Jane Watson, Allen Schirm and Ron Wasserstein, John Kruschke, and Kari Lock Morgan. I cajoled four of my graduate students (Jonathan Brown, Mike Huberty, Chelsey Legacy, and Vimal Rao) to tag along, and it was fun to see them interacting with the people and ideas presented.

Computing Talk at SSC 2018

I am giving a talk at the 46th Annual Meeting of the Statistical Society of Canada in Montreal on June 05, 2018. The talk is part of an invited session on Teaching Statistics to Graduate Students in the Health and Social Sciences. Information, including the slides, is available below. Title: Statistical Computing: Non-Ignorable Missingness in the Graduate-Level Social Science Curriculum Abstract: In 2010, Nolan and Temple Lang pointed out that "

Q&A with Becoming a Teacher of Statistics Class: Part IV

This post is the fourth (and last) in a series of blogposts in which I respond to questions from the students in the Becoming a Teacher of Statistics course. In today’s posting I respond to questions that asked me for predictions about the future of statistics teaching and statistics education research. Before I get into the Q&A, let me just state: Prediction is hard. Leland Wilkinson in The Future of Statistical Computing reminded us of this when he cited a prediction about computers that Andrew Hamilton made in a 1949 issue of Popular Mechanics

Statistics Education Research Seminar: Teaching Statistics from a Modeling Perspective

My colleague Robert delMas is teaching our doctoral-level research seminar, EPsy 8271 next fall, and it looks to be an interesting topic. The details about the course follow: EPSY 8271 | Statistics Education Research Seminar: Teaching Statistics from a Modeling Perspective (3 credits) Day/Time: Fridays, 9:00 a.m.–11:30 a.m. (Fall 2018) Location: 220 Wulling Hall Instructor: Robert delMas, Ph.D. This seminar will focus on research related to teaching introductory statistics through a modeling approach.