Skip to main content

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 219.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 279.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 279.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  • Behrens, J. T. (1997). Toward a theory and practice of using interactive graphics in statistics education. In J. B. Garfield & G. Burril (Eds.), Research on the role of technology in teaching and learning statistics: Proceedings of the 1996 International Association for Statistics Education (IASE) roundtable (pp. 111–122). Voorburg, The Netherlands: International Statistical Institute.

    Google Scholar 

  • Biggs, J. B., & Collis, K. F. (1982). Evaluating the quality of learning: The SOLO taxonomy. New York: Academic Press.

    Google Scholar 

  • Case, R. (1985). Intellectual development: From birth to adulthood. New York: Academic Press.

    Google Scholar 

  • Clement, J. (2000). Analysis of clinical interviews. In A. Kelly & R. Lesh (Eds.), Handbook of research design in mathematics and science education (pp. 547–589). Mahwah, NJ: Erlbaum.

    Google Scholar 

  • Cohen, S. (1997). ConStatS: Software for Conceptualizing Statistics. Tufts University: Software Curricular Studio. Retrieved April 23, 2003, from http://www.tufts.edu/tccs/services/css/ConStatS.html

  • Davenport, E. C. (1992). Creating data to explain statistical concepts: Seeing is believing. In Proceedings of the Section on Statistical Education of the American Statistical Association (pp. 389–394).

    Google Scholar 

  • delMas, R. (2001). Sampling SIM (version 5). Retrieved April 23, 2003, from http://www.gen.umn.edu/faculty_staff/delMas/stat_tools

  • delMas, R., Garfield, J., & Chance, B. (1998). Assessing the effects of a computer microworld on statistical reasoning. In L. Pereira-Mendoza, L. S. Kea, T. W. Kee, & W. Wong (Eds.), Proceedings of the Fifth International Conference on Teaching Statistics (pp. 1083–1089), Nanyang Technological University. Singapore: International Statistical Institute.

    Google Scholar 

  • delMas, R., Garfield, J., & Chance, B. (1999a). Assessing the effects of a computer microworld on statistical reasoning. Journal of Statistics Education, 7(3). Retrieved April 23, 2003, from http://www.amstat.org/publications/jse/secure/v7n3/delmas.cfm

  • delMas, R., Garfield, J., & Chance, B. (1999b). Exploring the role of computer simulations in developing understanding of sampling distributions. Paper presented at the Annual Meeting of the American Educational Research Association, Montreal, Canada.

    Google Scholar 

  • Doane, D. P., Tracy, R. L., & Mathieson, K. (2001). Visual Statistics, 2.0. New York: McGraw-Hill. Retrieved April 23, 2003, from http://www.mhhe.com/business/opsci/doane/show_flash_intro.html

    Google Scholar 

  • Earley, M. A. (2001). Improving statistics education through simulations: The case of the sampling distribution. Paper presented at the Annual Meeting of the Mid-Western Educational Research Association, Chicago, IL.

    Google Scholar 

  • Garfield, J. (2002). The challenge of developing statistical reasoning. Journal of Statistics Education, 10(3). Retrieved April 23, 2003, from http://www.amstat.org/publications/jse/

  • Garfield, J., delMas, R., & Chance, B. (1999). Developing statistical reasoning about sampling distributions. Presented at the First International Research Forum on Statistical Reasoning, Thinking, and Literacy (SRTL), Kibbutz Be’eri, Israel.

    Google Scholar 

  • Garfield, J., delMas, R., & Chance, B. (2002). Tools for teaching and assessing statistical inference [website]. Retrieved April 23, 2003, from: http://www.gen.umn.edu/faculty_staff/delmas/stat_tools/index.htm

  • Glencross, M. J. (1988). A practical approach to the Central Limit Theorem. In R. Davidson & J. Swift (Eds.), Proceedings of the second international conference on teaching statistics (pp. 91–95). Victoria, B.C.: Organizing Committee for the Second International Conference on Teaching Statistics.

    Google Scholar 

  • Hodgson, T. R. (1996). The effects of hands-on activities on students’ understanding of selected statistical concepts. In E. Jakubowski, D. Watkins, & H. Biske (Eds.), Proceedings of the Eighteenth Annual Meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education (pp. 241–246). Columbus, OH: ERIC Clearinghouse for Science, Mathematics, and Environmental Education.

    Google Scholar 

  • Hodgson, T. R., & Burke, M. (2000). On simulation and the teaching of statistics. Teaching Statistics, 22(3).

    Google Scholar 

  • Holland, J. H., Holyoak, K. J., Nisbett, R. E., & Thagard, P. R. (1987). Induction: Processes of inference, learning, and discovery. Cambridge, Mass.: MIT Press.

    Google Scholar 

  • Jennings, D., Amabile, T., & Ross, L. (1982). Informal covariation assessment: Data-based versus theory-based judgments. In D. Kahneman, P. Slovic, & A. Tversky (Eds.), Judgment under uncertainty: Heuristics and biases (pp. 211–230). Cambridge, UK: Cambridge University Press.

    Chapter  Google Scholar 

  • Jones, G. A., Langrall, C. W., Mooney, E. S., Wares, A. S., Jones, M. R., Perry, B., et al. (2001). Using students’ statistical thinking to inform instruction. Journal of Mathematical Behavior, 20, 109–144.

    Article  Google Scholar 

  • Jones, G. A., Thornton, C. A., Langrall, C. W., Mooney, E., Perry, B., & Putt, I. (2000). A framework for characterizing students’ statistical thinking. Mathematical Thinking and Learning, 2, 269–308.

    Article  Google Scholar 

  • Lane, D. M. (2001). Hyper Stat. Retrieved April 24, 2003, from http://davidmlane.com/hyperstat/

  • Lang, J., Coyne, G., & Wackerly, D. (1993), ExplorStat—Active Demonstration of Statistical Concepts, University of Florida. Retrieved April 24, 2003, from http://www.stat.ufl.edu/users/dwack/

  • Lord, C., Ross, L., & Lepper, M. (1979). Biased assimilation and attitude polarization: The effects of prior theories on subsequently considered evidence. Journal of Personality and Social Psychology, 37, 2098–2109.

    Article  Google Scholar 

  • Mills, J. D. (2002). Using computer simulation methods to teach statistics: A review of the literature. Journal of Statistics Education, 10(1). Retrieved April 24, 2003, from: http://www.amstat.org/publications/jse/v10n1/mills.html

  • Mooney, E. S. (2002). A framework for characterizing middle school students’ statistical thinking. Mathematical Thinking and Learning, 4(1), 23–63.

    Article  Google Scholar 

  • Moore, D. (2000). Basic Practice of Statistics. New York: Freeman.

    Google Scholar 

  • Moore, D., & McCabe, G. (2002). Introduction to the Practice of Statistics (4th ed.). New York: Freeman.

    Google Scholar 

  • Newton, H. J., & Harvill, J. L. (1997). Stat Concepts: A visual tour of statistical ideas (1st ed.). Pacific Grove, CA: Brooks/Cole.

    Google Scholar 

  • Nickerson, R. S. (1995). Can technology help teach for understanding? In D. N. Perkins, J. L. Schwartz, M. M. West, & M. S. Wiske (Eds.), Software goes to school: Teaching for understanding with new technologies (pp. 7–22). New York: Oxford University Press.

    Google Scholar 

  • Perkins, D. N., Crismond, D., Simmons, R., & Unger, C. (1995). Inside understanding. In D. N. Perkins, J. L. Schwartz, M. M. West, & M. S. Wiske (Eds.), Software goes to school: Teaching for understanding with new technologies (pp. 70–87). New York: Oxford University Press.

    Google Scholar 

  • Perkins, D. N., Schwartz, J. L., West, M. M., & Wiske, M. S. (Eds.). (1995). Software goes to school: Teaching for understanding with new technologies. New York: Oxford University Press.

    Google Scholar 

  • Posner, G. J., Strike, K. A., Hewson, P. W., & Gertzog, W. A. (1982). Accommodation of a scientific conception: Toward a theory of conceptual change. Science Education, 66(2), 211–227.

    Article  Google Scholar 

  • Ross, L., & Anderson, C. (1982). Shortcomings in the attribution process: On the origins and maintenance of erroneous social assessments. In D. Kahneman, P. Slovic, & A. Tversky (Eds.), Judgment under uncertainty: Heuristics and biases (pp. 129–152). Cambridge, UK: Cambridge University Press.

    Chapter  Google Scholar 

  • Saldanha, L. A., & Thompson, P. W. (2001). Students’ reasoning about sampling distributions and statistical inference. In R. Speiser & C. Maher (Eds.), Proceedings of The Twenty-Third Annual Meeting of the North American Chapter of the International Group for the Psychology of Mathematics Education (pp. 449–454), Snowbird, Utah. Columbus, Ohio: ERIC Clearinghouse.

    Google Scholar 

  • Schwarz, C. J., & Sutherland, J. (1997). An on-line workshop using a simple capture-recapture experiment to illustrate the concepts of a sampling distribution. Journal of Statistics Education, 5(1). Retrieved April 24, 2003, from http://www.amstat.org/publications/jse/v5n1/schwarz.html

  • Schwartz, D. L., Goldman, S. R., Vye, N. J., Barron, B. J., & the Cognition Technology Group at Vanderbilt. (1997). Aligning everyday and mathematical reasoning: The case of sampling assumptions. In S. Lajoie (Ed.), Reflections on statistics: Agendas for learning, teaching and assessment in K-12 (pp. 233–273). Hillsdale, NJ: Erlbaum.

    Google Scholar 

  • Sedlmeier, P. (1999). Improving statistical reasoning: Theoretical models and practical implications. Mahwah, NJ: Erlbaum.

    Google Scholar 

  • Siegel, A., & Morgan, C. (1996). Statistics and data analysis: An introduction (2nd ed.). New York: Wiley.

    MATH  Google Scholar 

  • Simon, J. L. (1994). What some puzzling problems teach about the theory of simulation and the use of resampling. American Statistician, 48(4), 290–293.

    Google Scholar 

  • Snir, J., Smith, C., & Grosslight, L. (1995). Conceptually enhanced simulations: A computer tool for science teaching. In D. N. Perkins, J. L. Schwartz, M. M. West, & M. S. Wiske (Eds.), Software goes to school: Teaching for understanding with new technologies (pp. 106–129). New York: Oxford University Press.

    Google Scholar 

  • Thomason, N., & Cummings, G. (1999). Stat Play. School of Psychological Science, La Trobe University, Bandora, Australia. Retrieved April 24, 2003, from: http://www.latrobe.edu.au/psy/cumming/statplay.html

    Google Scholar 

  • Velleman, P. (2003). Activ Stats, Ithaca, NY: Data Description, Inc. Retrieved April 24, 2003, from http://www.aw.com/catalog/academic/product/1,4096,0201782456,00.html

    Google Scholar 

  • Well, A. D., Pollatsek, A., & Boyce, S. J. (1990). Understanding the effects of sample size on the variability of the mean. Organizational Behavior and Human Decision Processes, 47, 289–312.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Kluwer Academic Publishers

About this chapter

Cite this chapter

Chance, B., del Mas, R., Garfield, J. (2004). Reasoning about Sampling Distribitions. In: Ben-Zvi, D., Garfield, J. (eds) The Challenge of Developing Statistical Literacy, Reasoning and Thinking. Springer, Dordrecht. https://doi.org/10.1007/1-4020-2278-6_13

Download citation

  • DOI: https://doi.org/10.1007/1-4020-2278-6_13

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-2277-7

  • Online ISBN: 978-1-4020-2278-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics