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Strategies for Managing Statistical Complexity with New Software Tools
ARTICLE

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Statistics Education Research Journal Volume 3, Number 2, ISSN 1570-1824

Abstract

New software tools for data analysis provide rich opportunities for representing and understanding data. However, little research has been done on how learners use these tools to think about data, nor how that affects teaching. This paper describes several ways that learners use new software tools to deal with variability in analyzing data, specifically in the context of comparing groups. The two methods we discuss are 1) reducing the apparent variability in a data set by grouping the values using numerical bins or cut points and 2) using proportions to interpret the relationship between bin size and group size. This work is based on our observations of middle- and high-school teachers in a professional development seminar, as well as of students in these teachers' classrooms, and in a 13-week sixth grade teaching experiment. We conclude with remarks on the implications of these uses of new software tools for research and teaching. (Contains 9 figures.)

Citation

Hammerman, J.K. & Rubin, A. (2004). Strategies for Managing Statistical Complexity with New Software Tools. Statistics Education Research Journal, 3(2), 17-41. Retrieved January 29, 2020 from .

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Cited By

View References & Citations Map
  • Teachers' statistical problem solving with dynamic technology: Research results across multiple institutions

    Hollylynne Lee, North Carolina State University, United States; Gladis Kersaint, University of South Florida, United States; Suzanne Harper, Miami University, United States; Shannon Driskell, University of Dayton, United States; Keith Leatham, Brigham Young University, United States

    Contemporary Issues in Technology and Teacher Education Vol. 12, No. 3 (September 2012) pp. 286–307

  • Prospective Teachers' Statistical Problem Solving with Dynamic Technology:

    Hollylynne S. Lee, North Carolina State University, United States; Gladis Kersaint, University of South Florida, United States; Suzanne R. Harper, Miami University, United States; Shannon O. S. Driskell, University of Dayton, United States; Keith Leatham, Brigham Young University, United States

    Society for Information Technology & Teacher Education International Conference 2012 (Mar 05, 2012) pp. 4925–4938

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