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Lee, Hollylynne S.; Starling, Tina T.; Gonzalez, Marggie D. – Mathematics Teacher, 2014
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…
Descriptors: Sampling, Sample Size, Statistical Distributions, Simulation
Stack, Sue; Watson, Jane – Australian Mathematics Teacher, 2013
There is considerable research on the difficulties students have in conceptualising individual concepts of probability and statistics (see for example, Bryant & Nunes, 2012; Jones, 2005). The unit of work developed for the action research project described in this article is specifically designed to address some of these in order to help…
Descriptors: Secondary School Mathematics, Grade 10, Mathematical Concepts, Probability
Menil, Violeta C.; Ye, Ruili – MathAMATYC Educator, 2012
This study serves as a teaching aid for teachers of introductory statistics. The aim of this study was limited to determining various sample sizes when estimating population proportion. Tables on sample sizes were generated using a C[superscript ++] program, which depends on population size, degree of precision or error level, and confidence…
Descriptors: Sample Size, Probability, Statistics, Sampling
Tabor, Josh – Journal of Statistics Education, 2010
On the 2009 AP[c] Statistics Exam, students were asked to create a statistic to measure skewness in a distribution. This paper explores several of the most popular student responses and evaluates which statistic performs best when sampling from various skewed populations. (Contains 8 figures, 3 tables, and 4 footnotes.)
Descriptors: Advanced Placement, Statistics, Tests, High School Students
Peer reviewedGordon, Florence – Mathematics and Computer Education, 1987
Sophisticated simulations using computer graphics can lead to students deducing virtually all conditions of the Central Limit Theorem. Eight graphs illustrate the discussion. (MNS)
Descriptors: College Mathematics, Computer Graphics, Computer Simulation, Graphs

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