The American Statistical Association (ASA) Statement of 2016 on Statistical Significance and P-value: A Critical Thought
Science Journal of Applied Mathematics and Statistics
Volume 5, Issue 1, February 2017, Pages: 41-48
Received: Dec. 6, 2016;
Accepted: Jan. 4, 2017;
Published: Jan. 24, 2017
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Silas Memory Madondo, Department of Research, Mount Meru University, Arusha, Tanzania
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A study on American Statistical Association (ASA) policy statement on statistical significance testing and p-value of 2016 was carried out in Tanzania. The purpose of the study was to explore the feelings and reactions of university statistics tutors towards the American Statistical Association policy statement on statistical significance testing and p-value of 2016. A sample of 9 statistics tutors from different disciplines were selected from public and private universities via heterogeneous purposive sampling to participate in the study. Respondents had mixed feelings towards ASA policy statement of 2016. The ASA policy statement was criticized for being shallow in depth, subjective and failing to answer the core problems raised against the use of Null Hypothesis Significance Testing (NHST) and p-value. The ASA policy statement was dismissed as a non event with nothing new to offer. However, despite being shallow, the ASA policy on NHST and p-value is likely to trigger a health debate on the shortfalls of NHST and p-value and the debate will eventually lead to a breakthrough.
American Statistical Association, Heterogeneous Purposive Sampling, Null Hypothesis Significance Testing, P-value, Null and Alternative Hypotheses
To cite this article
Silas Memory Madondo,
The American Statistical Association (ASA) Statement of 2016 on Statistical Significance and P-value: A Critical Thought, Science Journal of Applied Mathematics and Statistics.
Vol. 5, No. 1,
2017, pp. 41-48.
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/
) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
American Statistical Association Releases Statement on Statistical Significance and P-values, March 7, 2016.[http://amstat.tandfonline.com/doi/abs/10.1080/00031305.2016.1154108#.Vt2XIOaE2MN].
Curran-Everett, D. (2009). Explorations in Statistics: Hypothesis Tests and P-Values. AdvPhysioEduc,33, 81-86.
Cohen, J. (1990). Things I have learned (so far). American Psychologist, 45, 1304-1312.
Field, A. (2005). Effect Sizes-Statistics Hell. www.statisticshell.com>docs>effectsizes.
Wasserstein, R. L. &Lazar, N. A. (2016). The ASA's Statement on P-values: Context, Process, and Purpose. The American Statistician. DOI:10.1080/00031305.2016.1154108.
Nuzzo, R. (2014). Scientific Method: Statistical Errors. Nature, 506,150–152. Available at http://www.nature.com/news/scientific-methodstatistical-errors-1.14700. .
Siegfried, T. (2014). To Make Science Better, Watch out for Statistical Flaws. Science News Context Blog, February 7, 2014. Available at https://www.sciencenews.org/blog/context/make-science-betterwatch-out-statistical-flaws. .
Cumming, G. (2013). The Problem With p Values: HowSignificant are They, Really?. Available at http://phys.org/wire-news/EDITORIAL 131.145707973/the-problem-with-p-values-how-significant-are-they-really.html. .
Gelman, A., and Loken, E. (2014). The Statistical Crisis in Science [online]. American Scientist, 102. Available at http://www.americanscientist.org/issues/feature/2014/6/the-statistical-crisis-in-science.
Madondo, S. M. (2016). Essentials of Social Science Research. Mount Meru University, Tanzania.
Trafimow, D. &Marks, M. (2015). A Critical analysis of the Relevance of Inferential Statistics. Basic and Applied Social Psycology, 37 (1).
Creswell, J. W., & Clark, V. L. P., (2007). Designing and Conducting Mixed Methods Research. University of Nebraska-Lincoln: Sage Publications.