Editing Statistical hypothesis test (section)

==Education==
{{main|Statistics education}}

Statistics is increasingly being taught in schools with hypothesis testing being one of the elements taught.<ref>[http://www.corestandards.org/the-standards/mathematics/hs-statistics-and-probability/introduction/ Mathematics > High School: Statistics & Probability > Introduction] {{webarchive|url=https://archive.today/20120728122912/http://www.corestandards.org/the-standards/mathematics/hs-statistics-and-probability/introduction/|date=July 28, 2012}} Common Core State Standards Initiative (relates to USA students)</ref><ref>[http://www.collegeboard.com/student/testing/ap/sub_stats.html College Board Tests > AP: Subjects > Statistics] The College Board (relates to USA students)</ref> Many conclusions reported in the popular press (political opinion polls to medical studies) are based on statistics. Some writers have stated that statistical analysis of this kind allows for thinking clearly about problems involving mass data, as well as the effective reporting of trends and inferences from said data, but caution that writers for a broad public should have a solid understanding of the field in order to use the terms and concepts correctly.<ref name="Huff8">{{cite book|last=Huff|first=Darrell|url=https://archive.org/details/howtoliewithstat00huff/page/8|title=How to lie with statistics|publisher=Norton|year=1993|isbn=978-0-393-31072-6|location=New York|page=[https://archive.org/details/howtoliewithstat00huff/page/8 8]}}'Statistical methods and statistical terms are necessary in reporting the mass data of social and economic trends, business conditions, "opinion" polls, the census. But without writers who use the words with honesty and readers who know what they mean, the result can only be semantic nonsense.'</ref><ref name="S&C">{{cite book|last1=Snedecor|first1=George W.|title=Statistical Methods|last2=Cochran|first2=William G.|publisher=Iowa State University Press|year=1967|edition=6|location=Ames, Iowa|page=3}} "...the basic ideas in statistics assist us in thinking clearly about the problem, provide some guidance about the conditions that must be satisfied if sound inferences are to be made, and enable us to detect many inferences that have no good logical foundation."</ref> An introductory college statistics class places much emphasis on hypothesis testing – perhaps half of the course. Such fields as literature and divinity now include findings based on statistical analysis (see the [[Bible Analyzer]]). An introductory statistics class teaches hypothesis testing as a cookbook process. Hypothesis testing is also taught at the postgraduate level. Statisticians learn how to create good statistical test procedures (like ''z'', Student's ''t'', ''F'' and chi-squared). Statistical hypothesis testing is considered a mature area within statistics,<ref name="Lehmann97" /> but a limited amount of development continues.

An academic study states that the cookbook method of teaching introductory statistics leaves no time for history, philosophy or controversy. Hypothesis testing has been taught as received unified method. Surveys showed that graduates of the class were filled with philosophical misconceptions (on all aspects of statistical inference) that persisted among instructors.<ref>{{cite journal|last1=Sotos|first1=Ana Elisa Castro|last2=Vanhoof|first2=Stijn|last3=Noortgate|first3=Wim Van den|last4=Onghena|first4=Patrick|year=2007|title=Students' Misconceptions of Statistical Inference: A Review of the Empirical Evidence from Research on Statistics Education|url=https://lirias.kuleuven.be/bitstream/123456789/136347/1/CastroSotos.pdf|journal=Educational Research Review|volume=2|issue=2|pages=98–113|doi=10.1016/j.edurev.2007.04.001}}</ref> While the problem was addressed more than a decade ago,<ref>{{cite journal|last=Moore|first=David S.|year=1997|title=New Pedagogy and New Content: The Case of Statistics|url=http://www.stat.auckland.ac.nz/~iase/publications/isr/97.Moore.pdf|journal=International Statistical Review|volume=65|issue=2|pages=123–165|doi=10.2307/1403333|jstor=1403333}}</ref> and calls for educational reform continue,<ref>{{Cite journal |last1=Hubbard |first1=Raymond|last2=Armstrong|first2=J. Scott|author-link2=J. Scott Armstrong|year=2006|title=Why We Don't Really Know What Statistical Significance Means: Implications for Educators|journal=Journal of Marketing Education|volume=28 |issue=2|pages=114–120 |doi=10.1177/0273475306288399 |hdl-access=free |hdl=2092/413 |s2cid=34729227}}</ref> students still graduate from statistics classes holding fundamental misconceptions about hypothesis testing.<ref>{{cite journal|last1=Sotos|first1=Ana Elisa Castro|last2=Vanhoof|first2=Stijn|last3=Noortgate|first3=Wim Van den|last4=Onghena|first4=Patrick|year=2009|title=How Confident Are Students in Their Misconceptions about Hypothesis Tests?|journal=Journal of Statistics Education|volume=17|doi=10.1080/10691898.2009.11889514|doi-access=free|number=2}}</ref> Ideas for improving the teaching of hypothesis testing include encouraging students to search for statistical errors in published papers, teaching the history of statistics and emphasizing the controversy in a generally dry subject.<ref name="Gigerenzer 2004 391–408">{{cite book|last=Gigerenzer|first=G.|title=The SAGE Handbook of Quantitative Methodology for the Social Sciences|year=2004|isbn=9780761923596|pages=391–408|chapter=The Null Ritual What You Always Wanted to Know About Significant Testing but Were Afraid to Ask|doi=10.4135/9781412986311|chapter-url=http://library.mpib-berlin.mpg.de/ft/gg/GG_Null_2004.pdf}}</ref>

Raymond S. Nickerson commented:
{{block quote|The debate about NHST has its roots in unresolved disagreements among major contributors to the development of theories of inferential statistics on which modern approaches are based. [[Gigerenzer]] et al. (1989) have reviewed in considerable detail the controversy between R. A. Fisher on the one hand and Jerzy Neyman and Egon Pearson on the other as well as the disagreements between both of these views and those of the followers of Thomas Bayes. They noted the remarkable fact that little hint of the historical and ongoing controversy is to be found in most textbooks that are used to teach NHST to its potential users. The resulting lack of an accurate historical perspective and understanding of the complexity and sometimes controversial philosophical foundations of various approaches to statistical inference may go a long way toward explaining the apparent ease with which statistical tests are misused and misinterpreted.<ref name=nickerson />}}