The August 2019 issue of The American Statistician features a dozen articles that span a variety of interesting topics.
p-value
Real-World Significance Beyond P-Value: Leadership Forum Discusses Impact of Moving Beyond Statistical Significance
Presenters and panelists called for more volunteers to build the community of statistics and data science. Attendees shared their stories and sought advice from the panelists.
Statistics and Unintended Consequences
In her latest column, Karen Kafadar discusses how to communicate the importance of statistical inference and the proper interpretation of p-values.
P-Values: To Own or Not to Own?
In her latest column, Karen Kafadar discusses the debate about the value of hypothesis testing and the over-reliance on p-values as a cornerstone of statistical methodology.
February Issue Offers Variety of Topics
The February 2019 issue of The American Statistician features 13 articles.
‘Point-Oh-Five’: A Statistics Song
In honor of the 2017 ASA Symposium on Statistical Inference, ASA member Lawrence Lesser of The University of Texas at El Paso rewrote the Bee Gees’ Grammy-winning hit, Stayin’ Alive, to inspire discussion about the use of p-values and the 0.05 cutoff.
‘Lady Tasting Tea’ Author Publishes First Book in ASA/CRC Press Series
David Salsburg answers a few questions about his new book and what inspired him to write it.
ASA Leaders Reminisce: Ronald L. Wasserstein
In the 20th installment of the Amstat News series of interviews with ASA presidents and executive directors, we feature a discussion with current ASA Executive Director Ronald L. Wasserstein.
The Story Behind the ASA Statement on P-Values
For the past year, the ASA has had a committee working on elucidating principles that should accompany the use of p-values. I asked ASA executive director Ron Wasserstein to answer some questions about how this came about.
ASA Releases ‘Statement on Statistical Significance and P-Values’
The statement includes six principles underlying the proper use and interpretation of the p-value and is intended to improve the conduct and interpretation of quantitative science and inform the growing emphasis on reproducibility of science research.