Activity-Based Statistics

Scheaffer, Richard L.; Watkins, Ann Vreeland; Gnanadesikan, Mrudulla; Witmer, Jeffrey A.

doi:10.1007/978-1-4757-3843-8

Cited by 76 publications

(31 citation statements)

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“…AW: Dick Scheaffer had the vision for Activity-Based Statistics and put together a writing team of Jeff Witmer, Mrudulla Gnanadesikan, and me (Scheaffer et al 1996). The world of statistics education was much smaller in the 1990s and there was a lot of overlap in personnel from project to project.…”

Section: Ar: One Of the Ways That You've Had A Considerable Impact Onmentioning

confidence: 99%

Interview with Ann Watkins

Rossman

Watkins

2015

Journal of Statistics Education

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Section: Ar: One Of the Ways That You've Had A Considerable Impact Onmentioning

confidence: 99%

Interview with Ann Watkins

Rossman

Watkins

2015

Journal of Statistics Education

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“…It is widely recognized that if special purpose statistics courses are going to successfully promote active learning, they must provide students with concrete opportunities to work with real-life problems [1,2,5]. In addition, they should introduce students to the application of statistics to real-world problems, even if students have not gathered their own data.…”

Section: Learning Applied Statistics In Actionmentioning

confidence: 99%

An applied statistics course for systematics and ecology PhD students

Ojeda¹,

Sosa²

2002

International Journal of Mathematical Education in Science and

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Statistics education is under review at all educational levels. Statistical concepts, as well as the use of statistical methods and techniques, can be taught in at least two contrasting ways. Speci®cally, (1) teaching can be theoretically and mathematically oriented, or (2) it can be less mathematically oriented being focused, instead, on application and the use of data to solve real-world problems. The second approach is growing in practice and new goals have recently emerged. At present, statistics courses stress probability concepts, data analysis, and the interpretation and communication of results. Understanding the process of statistical investigation is established as a way of improving mastery of statistical reasoning. In this context, a project-based approach allows the design and implementation of participating learning scenarios in order to understand the statistical methodology and, as a consequence, improve research. This approach points out that statistics is a rational methodology used to solve practical problems. The purpose of this paper is to present the design and results of an applied statistics course for PhD students in ecology and systematics using a project-based approach. Examples involving character coding, species classi®cation, and the interpretation of geographical variation, which are the principal systematic analyses requiring statistical techniques, are presented using the results from student projects. In addition, an example from conservation ecology is presented. Results indicate that the students understood the concepts and applied the systematic and statistical techniques accurately using a data oriented approach.

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“…This activity is adapted from one for introductory statistics students, and the details may be found in Scheaffer et al (2004).…”

Section: Introducing Maximum Likelihood Estimation: Capture-recapturementioning

confidence: 99%

Fostering Conceptual Understanding in Mathematical Statistics

Green

Blankenship

2015

The American Statistician

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In many undergraduate statistics programs, the two-semester calculus-based mathematical statistics sequence is the cornerstone of the curriculum. However, ten years after the release of the Guidelines for the Assessment and Instruction in Statistics Education (GAISE) College Report (GAISE, 2005) and the subsequent movement to stress conceptual understanding and foster active learning in statistics classrooms, the sequence still remains a traditional, lectureintensive course. In this paper, we discuss various instructional approaches, activities and assessments that can be used to foster active learning and emphasize conceptual understanding while still covering the necessary theoretical content students need to be successful in subsequent statistics or actuarial science courses. In addition, we share student reflections on these course enhancements. The course revision we suggest doesn't require substantial changes in content, so other mathematical statistics instructors can implement these strategies without sacrificing concepts in probability and inference that are fundamental to the needs of their students. (Note: Supplementary materials, including code used to generate class plots and activity handouts, are available online.)

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Activity-Based Statistics

Cited by 76 publications

References 0 publications

Interview with Ann Watkins

Interview with Ann Watkins

An applied statistics course for systematics and ecology PhD students

Fostering Conceptual Understanding in Mathematical Statistics

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