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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
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Strayer, Jeremy F. – Mathematics Teacher, 2013
Statistical studies are referenced in the news every day, so frequently that people are sometimes skeptical of reported results. Often, no matter how large a sample size researchers use in their studies, people believe that the sample size is too small to make broad generalizations. The tasks presented in this article use simulations of repeated…
Descriptors: Sampling, Sample Size, Research Methodology, Statistical Analysis
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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
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Mulekar, Madhuri S.; Siegel, Murray H. – Mathematics Teacher, 2009
If students are to understand inferential statistics successfully, they must have a profound understanding of the nature of the sampling distribution. Specifically, they must comprehend the determination of the expected value and standard error of a sampling distribution as well as the meaning of the central limit theorem. Many students in a high…
Descriptors: Statistical Inference, Statistics, Sample Size, Error of Measurement