Data Collection

  • The page will calculate the following: Exact binomial probabilities, Approximation via the normal distribution, Approximation via the Poisson Distribution. This page will calculate and/or estimate binomial probabilities for situations of the general "k out of n" type, where k is the number of times a binomial outcome is observed or stipulated to occur, p is the probability that the outcome will occur on any particular occasion, q is the complementary probability (1-p) that the outcome will not occur on any particular occasion, and n is the number of occasions.

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  • Illustrates the central limit theorem by allowing the user to increase the number of samples in increments of 100, 1000, or 10000.

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  • This page generates a graph of the Chi-Square distribution and displays the associated probabilities. Users enter the degrees of freedom (between 1 and 20, inclusive) upon opening the page.

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  • This page calculates the standard error of a sampling distribution of sample means when users input the mean and standard deviation of the population and the sample size.

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  • This applet generates a graph of the sampling distribution of sample means and displays the probabilities associated with that distribution. Users enter the mean and standard deviation of the source population and the size of the samples. The applet also calculates the standard error of the sample means.

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  • A paper discussing the development of construct validity as applied to psychological studies.
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  • The first chapter of an online Introduction to Biostatistics course. Two lecture notes and a set of overheads are provided. Additionally, links for additional reading and exercises with solutions are provided.
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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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  • This website lists five different types of probability sampling, giving the advantages and disadvantages of each.
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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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