statistical reasoning

statistical reasoning

Reasoning from combinations of data to arrive at conclusions about what is true, false, likely, or improbable.
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Critique: Part of the ASA-CRC Series on Statistical Reasoning in Science and Society, "Data Visualization: Charts, Maps, and Interactive Graphics" is especially recommended reading for students considering a career in data science, analysts who wants to learn more about visualization, and managers of teams working with data.
Throughout the book, the author provides a perfect integration of research methods with statistical reasoning by illustrating the various kinds of relevant examples from actual studies.
The RMFII Project has developed evidence-based learning progressions in algebraic, geometric and statistical reasoning, which build on the former work on multiplicative thinking of the Scaffolding Numeracy in the Middle Years (SNMY) Project (Siemon, Breed, & Virgona, 2005).
Balan and Lamothe developed the textbook from their biostatistics lecture course introducing biology students to statistical reasoning and modeling that are of critical importance to the foundations of modern biology.
It is a game that combines statistical reasoning with bluffing.
In contrast, the probabilistic interpretation involves statistical reasoning; that is, it means reflecting on the statistical processes involved in the behavior of the p value when the null hypothesis is not rejected (Ben-Zvi & Garfield, 2004).
Fundamentals of Statistical Reasoning in Education, 4th Edition
Braude argues that these ideas led to a mathematical abstraction that created a tension between statistical reasoning and intuition which continues to bedevil clinical medicine.
The statistics education research community has been discussing the lead in to inference, through informal inference, for some time, and for example the fifth Statistical Reasoning, Thinking and Literacy Forum (SRTL-5 in 2005) had informal inferential reasoning as its theme.
A survey of 162 articles in three journals of statistics education from 2005 through 2009 indicated the following topics, with percentages of total topic presentations indicated in parentheses (van der Merwe & Wilkinson, 2010): teaching and learning (29%), statistical reasoning (25%), computer use (15%), course design (12%), non-cognitive factors (10%), and non-empirical studies (9%).
In sampling and sample representativeness, students' responses on following item in the SLAS as shown below revealed several misconceptions evident in their statistical reasoning.
That study, has been criticized by many, including the National Highway Traffic Safety Administration, because of flawed statistical reasoning. "Additionally, helmet technology has significantly improved since that time - now helmets are much lighter but even sturdier and more protective" Haider says.
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