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  • A computer intensive introductory course for graduate students. A veritable online course with Powerpoint and Excel downloadable files for viewing. Also provides related outside links for further investigation on related topics.
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  • The GAISE project was funded by a Strategic Initiative Grant from ASA in 2003 to develop ASA-endorsed guidelines for assessment and instruction in statistics in the K-12 curriculum and for the introductory college statistics course.
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  • This section in the Engineering Statistics Handbook takes a data set and walks the user through analysis and experimental design based on the data.
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  • This section of the Engineering Statistics Handbook describes in detail the process of choosing an experimental design to obtain the results you need. The basic designs an engineer needs to know about are described in detail.
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  • This website provides lesson plans, activities, a problem bank, and links to references that meet NCTM standards for probability.
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  • This JAVA applet is designed to give students practice in calculating basic probabilities using the binomial distribution. The applet gives students short problem descriptions that require a binomial probability to solve. The user is then prompted to follow a step by step process to find the probability. Users must answer a step correctly before the applet will allow them to move on to the next step. The page also gives further exercises that allow the user to think about binomial distributions more deeply and gives a link to a more detailed information about the binomial distribution.
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  • This article addresses the reporting of meta-analyses of observational studies in order to aid authors, reviewers, editors and readers when reading or writing such reports.
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  • This website lists five different types of probability sampling, giving the advantages and disadvantages of each.
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  • A series of pamphlets place online by the American Statistical Association, Survey Research Methods Section. Each pamphlet deals with a different aspect of survey research and how it is done.
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  • The larger the degrees of freedom, the closer the t-density is to the normal density. This reflects the fact that the standard deviation s approaches for large sample size n. You can visualize this in the given applet by moving the sliders.
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