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Replication and p intervals: p values predict the future only vaguely, but confidence intervals do much better. Perspect Psychol Sci (2008
"... ABSTRACT—Replication is fundamental to science, so statistical analysis should give information about replication. Because p values dominate statistical analysis in psychology, it is important to ask what p says about replication. The answer to this question is ‘‘Surprisingly little.’ ’ In one sim ..."
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ABSTRACT—Replication is fundamental to science, so statistical analysis should give information about replication. Because p values dominate statistical analysis in psychology, it is important to ask what p says about replication. The answer to this question is ‘‘Surprisingly little.’ ’ In one simulation of 25 repetitions of a typical experiment, p varied from <.001 to.76, thus illustrating that p is a very unreliable measure. This article shows that, if an initial experiment results in twotailed p 5.05, there is an 80% chance the onetailed p value from a replication will fall in the interval (.00008,.44), a 10 % chance that p <.00008, and fully a 10 % chance that p>.44. Remarkably, the interval—termed a p interval—is this wide however large the sample size. p is so unreliable and gives such dramatically vague information that it is a poor basis for inference. Confidence intervals, however, give much better information about replication. Researchers should minimize the role of p by using confidence intervals and modelfitting techniques and by adopting metaanalytic thinking. [p values] can be highly misleading measures of the evidence... against the null hypothesis.
The null ritual: What you always wanted to know about null hypothesis testing but were afraid to ask
 Handbook on Quantitative Methods in the Social Sciences. Sage, Thousand Oaks, CA
, 2004
"... No scientific worker has a fixed level of significance at which from year to year, and in all circumstances, he rejects hypotheses; he rather gives his mind to each particular case in the light of his evidence and his ideas. (Ronald A. Fisher, 1956, p. 42) It is tempting, if the only tool you have i ..."
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No scientific worker has a fixed level of significance at which from year to year, and in all circumstances, he rejects hypotheses; he rather gives his mind to each particular case in the light of his evidence and his ideas. (Ronald A. Fisher, 1956, p. 42) It is tempting, if the only tool you have is a hammer, to treat everything as if it were a nail. (A. H. Maslow, 1966, pp. 15–16) One of us once had a student who ran an experiment for his thesis. Let us call him Pogo. Pogo had an experimental group and a control group and found that the means of both groups were exactly the same. He believed it would be unscientific to simply state this result; he was anxious to do a significance test. The result of the test was that the two means did not differ significantly, which Pogo reported in his thesis. In 1962, Jacob Cohen reported that the experiments published in a major psychology journal had, on average, only a 50: 50 chance of detecting a mediumsized effect if there was one. That is, the statistical power was as low as 50%. This result was widely cited, but did it change researchers’ practice? Sedlmeier and Gigerenzer (1989) checked the studies in the same journal, 24 years later, a time period that should allow for change. Yet only 2 out of 64 researchers mentioned power,
20 STATISTICAL COGNITION: TOWARDS EVIDENCEBASED PRACTICE IN STATISTICS AND STATISTICS EDUCATION 4
"... Practitioners and teachers should be able to justify their chosen techniques by taking into account research results: This is evidencebased practice (EBP). We argue that, specifically, statistical practice and statistics education should be guided by evidence, and we propose statistical cognition ( ..."
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Practitioners and teachers should be able to justify their chosen techniques by taking into account research results: This is evidencebased practice (EBP). We argue that, specifically, statistical practice and statistics education should be guided by evidence, and we propose statistical cognition (SC) as an integration of theory, research, and application to support EBP. SC is an interdisciplinary research field, and a way of thinking. We identify three facets of SC—normative, descriptive, and prescriptive— and discuss their mutual influences. Unfortunately, the three components are studied by somewhat separate groups of scholars, who publish in different journals. These separations impede the implementation of EBP. SC, however, integrates the facets and provides a basis for EBP in statistical practice and education.
How to confuse with statistics. The use and misuse of conditional probabilities
 Statistical Science
, 2005
"... Abstract. This article shows by various examples how consumers of statistical information may be confused when this information is presented in terms of conditional probabilities. It also shows how this confusion helps others to lie with statistics, and it suggests both confusion and lies can be exp ..."
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Abstract. This article shows by various examples how consumers of statistical information may be confused when this information is presented in terms of conditional probabilities. It also shows how this confusion helps others to lie with statistics, and it suggests both confusion and lies can be exposed by using alternative modes of conveying statistical information. Key words and phrases: Conditional probabilities, natural frequencies, heuristical reasoning. 1.
Why figures with error bars should replace p values: Some conceptual arguments and empirical demonstrations. Zeitschrift für Psychologie
, 2009
"... Abstract. Nullhypothesis significance testing (NHST) is the primary means by which data are analyzed and conclusions made, particularly in the social sciences, but in other sciences as well (notably ecology and economics). Despite this supremacy however, numerous problems exist with NHST as a mean ..."
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Abstract. Nullhypothesis significance testing (NHST) is the primary means by which data are analyzed and conclusions made, particularly in the social sciences, but in other sciences as well (notably ecology and economics). Despite this supremacy however, numerous problems exist with NHST as a means of interpreting and understanding data. These problems have been articulated by various observers over the years, but are being taken seriously by researchers only slowly, if at all, as evidenced by the continuing emphasis on NHST in statistics classes, statistics textbooks, editorial policies and, of course, the daytoday practices reported in empirical articles themselves (Cumming et al., 2007). Over the past several decades, observers have suggested a simpler approach – plotting the data with appropriate confidence intervals (CIs) around relevant sample statistics – to supplement or take the place of hypothesis testing. This article addresses these issues.
Students ’ Understanding of Statistical Inference: Implications for Teaching
"... This thesis contains no material which has been accepted for a degree or diploma by the University or any other institution, except by way of background information and duly acknowledged in the thesis, and to the best of my knowledge and belief no material previously published or written by another ..."
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This thesis contains no material which has been accepted for a degree or diploma by the University or any other institution, except by way of background information and duly acknowledged in the thesis, and to the best of my knowledge and belief no material previously published or written by another person except where due acknowledgement is made in the text of the thesis, nor does the thesis contain any material that infringes copyright. iii This thesis may be made available for loan and limited copying in accordance
Teaching Confidence Intervals: Problems and Potential Solutions
"... There are benefits of teaching inference via confidence intervals (CIs), rather than null hypothesis significance testing (NHST). However, CIs are not without misconceptions. First, we provide empirical evidence that CI presentations of data can help alleviate some typical misinterpretations of resu ..."
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There are benefits of teaching inference via confidence intervals (CIs), rather than null hypothesis significance testing (NHST). However, CIs are not without misconceptions. First, we provide empirical evidence that CI presentations of data can help alleviate some typical misinterpretations of results, leading to more accurate conclusions and more justified
THE AMERICAN PSYCHOLOGICAL ASSOCIATION PUBLICATION MANUAL SIXTH EDITION: IMPLICATIONS FOR STATISTICS EDUCATION
"... The American Psychological Association (APA) Publication Manual sets the editorial standards for over 1000 journals in the behavioural, life and social sciences. Well known for its referencing standards, the Manual is also an authoritative source of statistical advice for many journals. It is theref ..."
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The American Psychological Association (APA) Publication Manual sets the editorial standards for over 1000 journals in the behavioural, life and social sciences. Well known for its referencing standards, the Manual is also an authoritative source of statistical advice for many journals. It is therefore crucial that statistics education in these disciplines address its requirements and recommendations. The sixth edition of the Manual (published 2010) includes new guidelines about reporting effect sizes, confidence intervals and metaanalysis. These changes are a response to calls for the statistical reform of psychology—in particular, calls to decrease reliance on Null Hypothesis Significance Testing—which have been made with increasing vigor over the last 60 years. This paper critically reviews the new guidelines and discusses the implications for statistics teaching within psychology and other disciplines. In addition to the 59 journals published by the American Psychological Association (APA), there are “at least a thousand other journals in psychology, the behavioural sciences, nursing and personnel administration [that] use the Manual as their style guide ” (APA, 2001, p. xxi). It is “the single text which virtually every psychologist, of whatever subspeciality, has contact with at some point in their career ” (Budge & Katz, 1995, p. 218). Best known for its advice on formatting and
The Effect of StudentDriven Projects on the Development of Statistical Reasoning. Doctoral Dissertation. Unniversity of Pittsburgh
, 2010
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, 2010
"... Confidence intervals permit, but do not guarantee, better ..."
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Confidence intervals permit, but do not guarantee, better