100 Questions (and Answers) About Statistics最新文献

What Are the Steps in Applying a Statistical Test to a Research Hypothesis? 对研究假设应用统计检验的步骤是什么?

100 Questions (and Answers) About Statistics Pub Date : 1900-01-01 DOI: 10.4135/9781483372334.n77

引用次数: 0

What Is a Research Hypothesis, and How Is It Used? 什么是研究假设?如何使用研究假设?

100 Questions (and Answers) About Statistics Pub Date : 1900-01-01 DOI: 10.4135/9781483372334.n64

引用次数: 0

What Is Effect Size, and Why Is It Important? 什么是效应大小，为什么它很重要?

100 Questions (and Answers) About Statistics Pub Date : 1900-01-01 DOI: 10.4135/9781483372334.n91

R. Coe

{"title":"What Is Effect Size, and Why Is It Important?","authors":"R. Coe","doi":"10.4135/9781483372334.n91","DOIUrl":"https://doi.org/10.4135/9781483372334.n91","url":null,"abstract":"Effect size is a simple way of quantifying the difference between two groups that has many advantages over the use of tests of statistical significance alone. Effect size emphasises the size of the difference rather than confounding this with sample size. However, primary reports rarely mention effect sizes and few textbooks, research methods courses or computer packages address the concept. This paper provides an explication of what an effect size is, how it is calculated and how it can be interpreted. focus for their campaign. Every 'Effect size' is simply a way of quantifying the size of the difference between two groups. It is easy to calculate, readily understood and can be applied to any measured outcome in Education or Social Science. It is particularly valuable for quantifying the effectiveness of a particular intervention, relative to some comparison. It allows us to move beyond the simplistic, 'Does it work or not?' to the far more sophisticated, 'How well does it work in a range of contexts?' Moreover, by placing the emphasis on the most important aspect of an intervention the size of the effect rather than its statistical significance (which conflates effect size and sample size), it promotes a more scientific approach to the accumulation of knowledge. For these reasons, effect size is an important tool in reporting and interpreting effectiveness. The routine use of effect sizes, however, has generally been limited to metaanalysis for combining and comparing estimates from different studies and is all too rare in original reports of educational research (Keselman et al., 1998). This is despite the fact that measures of effect size have been available for at least 60 years (Huberty, 2002), and the American Psychological Association has been officially encouraging authors to report effect sizes since 1994 but with limited success (Wilkinson et al., 1999). Formulae for the calculation of effect sizes do not appear in most statistics text books (other than those devoted to meta-analysis), are not featured in many statistics computer packages and are seldom taught in standard research methods courses. For these reasons, even the researcher who is convinced by the wisdom of using measures of effect size, and is not afraid to confront the orthodoxy of conventional practice, may find that it is quite hard to know exactly how to do so. The following guide is written for non-statisticians, though inevitably some equations and technical language have been used. It describes what effect size is, what it means, how it can be used and some potential problems associated with using it. 1. Why do we need 'effect size'? Consider an experiment conducted by Dowson (2000) to investigate time of day effects on learning: do children learn better in the morning or afternoon? A group of 38 children were included in the experiment. Half were randomly allocated to listen to a story and answer questions about it (on tape) at 9am, the other half to hear exactly t","PeriodicalId":289853,"journal":{"name":"100 Questions (and Answers) About Statistics","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123695840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

How Can Excel Be Used to Compute Measures of Central Tendency? 如何使用Excel计算集中趋势的度量?

100 Questions (and Answers) About Statistics Pub Date : 1900-01-01 DOI: 10.4135/9781483372334.n16

引用次数: 0

What Are Some Important Things to Remember About Understanding and Using Correlation Coefficients? 在理解和使用相关系数时需要记住哪些重要的事情?

100 Questions (and Answers) About Statistics Pub Date : 1900-01-01 DOI: 10.4135/9781483372334.n48

引用次数: 0

How Do I Know Which Statistical Test to Use? 我如何知道使用哪个统计检验?

100 Questions (and Answers) About Statistics Pub Date : 1900-01-01 DOI: 10.4135/9781483372334.n81

引用次数: 0

What Is the Coefficient of Determination, and How Is It Computed? 什么是决定系数，它是如何计算的?

100 Questions (and Answers) About Statistics Pub Date : 1900-01-01 DOI: 10.4135/9781483372334.n47

引用次数: 0

How Can the Reliability of a Test Be Increased? 如何提高测试的可靠性?

100 Questions (and Answers) About Statistics Pub Date : 1900-01-01 DOI: 10.4135/9781483372334.n55

引用次数: 0

What Is the Median, and How Is It Computed? 什么是中位数，它是如何计算的?

100 Questions (and Answers) About Statistics Pub Date : 1900-01-01 DOI: 10.4135/9781483372334.n11

引用次数: 0

How Do I Compute a Correlation Coefficient? 如何计算相关系数?

100 Questions (and Answers) About Statistics Pub Date : 1900-01-01 DOI: 10.4135/9781483372334.n44

引用次数: 0