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- W97532959 abstract "Statistical literacy is becoming a graduation requirement for many reasons. Yet most introductory courses focus just on descriptive statistics and statistical inference. In so doing, the importance of probability and chance (statistical inference) is overemphasized while the role of bias and the importance of interpreting tables and charts is under-emphasized. To be statistically literate, students must also understand probability as measuring strength of belief (Bayesian) and the use of observational studies to strengthen belief in causality (evidential statistics). Evidential statistics studies the use of statistics as evidence in supporting the truth of claims involving causal explanations and predictions. Studying evidential statistics is helpful in understanding statistical arguments in business, medicine, insurance, public affairs, law and epidemiology. Evidential statistics deals with the ambiguities of language and subtle distinctions involving conditional logic and the role of chance. Functionally, the relation between traditional statistics and evidential statistics is like that between micro and macroeconomics or between formal logic and practical reasoning (critical thinking). Students need an introduction to both traditional and evidential statistics. Sources of evidential statistics are reviewed along with arguments for and against teaching this new subject." @default.
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- W97532959 title "Statistical literacy and evidential statistics." @default.
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