Curriculum

  • This resource explains margin of error using an example on presidential popularity polls.
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  • This resource gives 3 questions readers should ask when presented with data and why to ask them: Where did the data come from? Have the data been peer-reviewed? How were the data collected? This page also describes why readers should: be skeptical when dealing with comparisons, and be aware of numbers taken out of context.

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  • This resource discusses sample sizes and how they are chosen.
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  • This resource explains the t-distribution and hypothesis testing (informally) using an example on laptop quality.
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  • This website is compilation of data from sources such as the CIA World Factbook, UN, and OECD. You can generate maps and graphs to statistically compare and research Nations.

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  • This textbook for medical statistics covers many topics such as: Data display and summary; Mean and standard deviation; Populations and samples; Statements of probability and confidence intervals; Differences between means: type I and type II errors and power; Differences between percentages and paired alternatives; The t tests; The chi-squared tests; Exact probabilty test; Rank score tests; Correlation and regression; Survival analysis; Study design and choosing a statistical test.
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  • This applet allows students to explore three methods for measuring "goodness of fit" of a linear model. Users can manipulate both the data and the regression line to see changes in the square error, the absolute error, and the shortest distance from the data point to the regression line.
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  • This lesson poses a series of questions designed to challenge students' possible misconceptions of statistical inference and hypothesis testing. The lesson uses the statistical software, Fathom, and three datasets with information on the number of chips per canister distributed by a snack maker. The data can found at the relation address below.
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  • This module discusses the probability of an event and relative frequency. The applet shows how empirical probability converges to theoretical probability as the sample size increases. The follow-up example includes an applet that simulates drawing differently colored balls from an urn.
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  • This collection of datasets comes from several phases of drug research. Each dataset comes with a full description and questions to answer from the data.
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