Using Data to Motivate the Use of Empirical Sampling Distributions

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Hollylynne S. Lee
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Tina T. Starling
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Marggie D. Gonzalez
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Research shows that students often struggle with understanding empirical sampling distributions. Using hands-on and technology models and simulations of problems generated by real data help students begin to make connections between repeated sampling, sample size, distribution, variation, and center. A task to assist teachers in implementing research-based strategies is included.

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Footnotes

Edited by Margaret Kinzel, mkinzel@boisestate.edu Boise State University, Boise, ID

Laurie Cavey, lauriecavey@boisestate.edu Boise State University, Boise, ID

Contributor Notes

Hollylynne S. Lee, hollylynne_lee@ncsu.edu, and Tina T. Starling, tina_starling@ncsu.edu, are colleagues in the Science, Technology, Engineering, and Mathematics Education Department at North Carolina State University in Raleigh.

Marggie D. Gonzalez, mdgonza2@ncsu.edu, is a doctoral candidate at North Carolina State University. All are interested in students' reasoning about statistical ideas when using technology tools and how secondary school mathematics teachers effectively use such tools with students during instruction and assessment.

(Corresponding author is Lee hollylynne_lee@ncsu.edu)
(Corresponding author is Starling tina_starling@ncsu.edu)
(Corresponding author is Gonzalez mdgonza2@ncsu.edu)
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