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首页> 外文会议>International Association for Statistical Education International Conferences on Teaching Statistics >STATISTICS EDUCATION IN THE SOCIAL AND BEHAVIOURAL SCIENCES: FROM DICHOTOMOUS THINKING TO ESTIMATION THINKING AND META-ANALYTIC THINKING
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STATISTICS EDUCATION IN THE SOCIAL AND BEHAVIOURAL SCIENCES: FROM DICHOTOMOUS THINKING TO ESTIMATION THINKING AND META-ANALYTIC THINKING

机译：社会与行为科学的统计教育：从二分法思维估算思维和荟萃分析思维

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摘要

Null hypothesis significant testing (NHST) dominates in the social and behavioural sciences, despite strong evidence of its disadvantages. Worst may be its reinforcement of dichotomous thinking (DT), which focuses on impoverished reject or don't-reject decisions. By contrast, estimation thinking (ET) and meta-analytic thinking (MAT) focus on sizes of effects, and cumulation of evidence to increase precision. A shift from DT to ET and MAT is highly desirable. Statistics education for ET and MAT will emphasise effect sizes, confidence intervals and metaanalysis, starting with the introductory course. Interpretation of confidence intervals should emphasise estimation, not NHST. Students and researchers, when specifying research goals, or discussing and interpreting findings, should use language that reflects ET and MAT. The outcome should be more quantitative theories, more sophisticated disciplines and better research progress.
机译：尽管有很大的证据证明了其缺点，所以无效假设大量测试（NHST）在社会和行为科学中占主导地位。最糟糕的可能是它的加强二分思维（DT），专注于贫困拒绝或不拒绝决策。相比之下，估计思维（et）和荟萃分析思想（Mat）专注于效果的大小，并累积证据提高精度。从DT到ET和垫的偏移是非常理想的。 ET和MAT的统计教育将强调与介绍性课程开始的影响，置信区间和元分析。置信间隔的解释应该强调估计，而不是NHST。学生和研究人员在指定研究目标或讨论和解释结果时，应该使用反映ET和垫的语言。结果应更加定量理论，更复杂的学科和更好的研究进展。

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