Conceptual Challenges in Coordinating Theoretical and Data-centered Estimates of Probability

Date

2011-01-01

Author

Konold, Cliff
Madden, Sandra
Pollatsek, Alexander
Pfannkuch, Maxine
Wild, Chris
Ziedins, Ilze
Finzer, William
Horton, Nicholas J.
Kazak, Sibel

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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A core component of informal statistical inference is the recognition that judgments based on sample data are inherently uncertain. This implies that instruction aimed at developing informal inference needs to foster basic probabilistic reasoning. In this article, we analyze and critique the now-common practice of introducing students to both "theoretical" and "experimental" probability, typically with the hope that students will come to see the latter as converging on the former as the number of observations grows. On the surface of it, this approach would seem to fit well with objectives in teaching informal inference. However, our in-depth analysis of one eighth-grader's reasoning about experimental and theoretical probabilities points to various pitfalls in this approach. We offer tentative recommendations about how some of these issues might be addressed.

URI

https://hdl.handle.net/11511/100748

Journal

MATHEMATICAL THINKING AND LEARNING

DOI

https://doi.org/10.1080/10986065.2011.538299

Collections

Department of Mathematics and Science Education, Article

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Citation Formats

C. Konold et al., “Conceptual Challenges in Coordinating Theoretical and Data-centered Estimates of Probability,” MATHEMATICAL THINKING AND LEARNING, vol. 13, no. 1-2, pp. 68–86, 2011, Accessed: 00, 2022. [Online]. Available: https://hdl.handle.net/11511/100748.