%0 Journal Article %1 CurranEverett2009 %A Curran-Everett, Douglas %D 2009 %J Advances in physiology education %K Algorithms ResearchDesign ResearchDesign:statistics&numericaldata ResearchDesign:trends StatisticsasTopic StatisticsasTopic:methods StatisticsasTopic:trends %N 2 %P 81-6 %R 10.1152/advan.90218.2008 %T Explorations in statistics: hypothesis tests and P values. %U http://www.ncbi.nlm.nih.gov/pubmed/19509391 %V 33 %X Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This second installment of Explorations in Statistics delves into test statistics and P values, two concepts fundamental to the test of a scientific null hypothesis. The essence of a test statistic is that it compares what we observe in the experiment to what we expect to see if the null hypothesis is true. The P value associated with the magnitude of that test statistic answers this question: if the null hypothesis is true, what proportion of possible values of the test statistic are at least as extreme as the one I got? Although statisticians continue to stress the limitations of hypothesis tests, there are two realities we must acknowledge: hypothesis tests are ingrained within science, and the simple test of a null hypothesis can be useful. As a result, it behooves us to explore the notions of hypothesis tests, test statistics, and P values.

@article{CurranEverett2009, abstract = {Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This second installment of Explorations in Statistics delves into test statistics and P values, two concepts fundamental to the test of a scientific null hypothesis. The essence of a test statistic is that it compares what we observe in the experiment to what we expect to see if the null hypothesis is true. The P value associated with the magnitude of that test statistic answers this question: if the null hypothesis is true, what proportion of possible values of the test statistic are at least as extreme as the one I got? Although statisticians continue to stress the limitations of hypothesis tests, there are two realities we must acknowledge: hypothesis tests are ingrained within science, and the simple test of a null hypothesis can be useful. As a result, it behooves us to explore the notions of hypothesis tests, test statistics, and P values.}, added-at = {2023-02-03T11:44:35.000+0100}, author = {Curran-Everett, Douglas}, biburl = {https://www.bibsonomy.org/bibtex/27cedd5b3bace6c9ca8ca24fac8156600/jepcastel}, doi = {10.1152/advan.90218.2008}, interhash = {80fad6af0464f39d2d7fd26dea641fc7}, intrahash = {7cedd5b3bace6c9ca8ca24fac8156600}, issn = {1522-1229}, journal = {Advances in physiology education}, keywords = {Algorithms ResearchDesign ResearchDesign:statistics&numericaldata ResearchDesign:trends StatisticsasTopic StatisticsasTopic:methods StatisticsasTopic:trends}, month = {6}, note = {Anàlisi de dades; Significació estadística; Introductori}, number = 2, pages = {81-6}, pmid = {19509391}, timestamp = {2023-02-03T11:44:35.000+0100}, title = {Explorations in statistics: hypothesis tests and P values.}, url = {http://www.ncbi.nlm.nih.gov/pubmed/19509391}, volume = 33, year = 2009 }