2020
DOI: 10.1080/10691898.2019.1696257
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Writing Assignments to Assess Statistical Thinking

Abstract: One of the main goals of statistics is to use data to provide evidence in support of an argument. This article will discuss some popular forms of writing assessments currently in use, to demonstrate the differences between the methods for structuring the students' learning to support their arguments with evidence. We share a model, which was originally created to assess students in introductory statistics and has been adapted for the second course in statistics, which takes a unique approach toward assessing t… Show more

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Cited by 21 publications
(12 citation statements)
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“…In this study, we could not observe the application of the Chi-square statistic with the continuity correction factor. This situation is similar to other studies that propose activities to work the Chi-square tests with students [61][62][63][64]. For example, Gibbs and Goossens [64] talk about the relevance of the continuity correction factor and that it is usually not used when working with software because some (e.g., Minitab) do not have the option to use this factor.…”
Section: Final Reflectionssupporting
confidence: 67%
“…In this study, we could not observe the application of the Chi-square statistic with the continuity correction factor. This situation is similar to other studies that propose activities to work the Chi-square tests with students [61][62][63][64]. For example, Gibbs and Goossens [64] talk about the relevance of the continuity correction factor and that it is usually not used when working with software because some (e.g., Minitab) do not have the option to use this factor.…”
Section: Final Reflectionssupporting
confidence: 67%
“…Although science and numbers appear objective on the surface, knowledge sharing in scientific fields, including data science, is essentially based on an argument and requires attention to elements of both style and rhetoric (Sutton, 1997;Woodard et al, 2020). A data-driven argument convinces someone of the validity of the findings, the appropriateness of the analysis, the generalizability of the conclusions, and the overall credibility of the evidence presented.…”
Section: Data Science Portfolios and Their Strengthsmentioning
confidence: 99%
“…In this sense, diverse authors (e.g., Woodard et al 2020;Fellers and Kuiper 2020;DePaolo et al 2016;Seier 2014;Gibbs and Goossens 2013;Leigh and Dowling 2010), have reported activities or problems proposals with the finality to make more accessible the study of the 2 tests, goodness-of-fit, independence, and homogeneity, which correspond to the problem areas presented in the previous section. However, commonly, in these investigations, the last partial meanings of each problem area (i.e., PM3, PM7 y PM11) were used.…”
Section: Incidence Of Partial Meanings Identified For the Statistical Education Researchmentioning
confidence: 99%