Continuous

  • This applet allows users to input their own data and perform one- and two-way Analyses of Variance. Key Word: ANOVA.

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  • This calculator determines the level of significance for the Wilcoxon-Mann-Whitney U-statistic. Users can enter N1, N2, and U or simply enter the raw data.

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  • This applet allows users to draw a curve on a graph, and then displays the polynomial fit of the curve.
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  • This collection of datasets from Princeton University each come with detailed descriptions of the data's history, how it was collected, and the data quality. Scroll down to "OPR Data Catalog Search" and either type your search terms into the search box or click "complete listings" to browse the archive. Data is available in text format.
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  • This is the homepage for the Reserve Bank of Australia. Browse data by Alphabetical Index of Statistics, Statistics by Frequency of Publication, or Bulletin Statistical Tables.
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  • Song includes vocabulary from fitting models, including outliers and assumptions. May be sung to tune of "You've Got Your Models" (The Fortunes). Musical accompaniment realization and vocals are by Joshua Lintz from University of Texas at El Paso.
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  • Song playfully celebrates Bayesian inference and includes various vocabulary such as coherence, prior, and exchangeable. May be sung to the tune of "Strangers in the Night" (Kaenpfert/Singleton/Snyder). Musical accompaniment realization and vocals are by Joshua Lintz from University of Texas at El Paso.
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  • Song celebrates Bayesian inference, includes verbal form of Bayes theorem. The lyrics were written by David Blackwell, University of California at Berkeley. May be sung to the tune of "Who (Stole My Heart Away)?" (Jerome Kern).  The audio was produced by Nicolas Acedo with vocals by Abeni Merriweather, both students in the Commercial Music Program at The University of Texas at El Paso.

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  • This tutorial provides a basic introduction to many topics in statistics and probability. Topics include: Sets and subsets, Statistical experiments, Counting, Basic probability rules, Bayes' theorem, Probability distributions, Discrete vs. Continuous, Binomial, Negative Binomial, Hypergeometric, Multinomial, Poisson, Normal, Sampling theory, Central tendency, Variability, Sampling distributions, t Distribution, Chi-Square Distribution, F Distribution, Estimation problems, Hypothesis testing, Power, Survey sampling, Simple random samples, Stratified samples, Cluster samples, Sample size.
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  • Everyday we have specific routines we engage in. Many of these routines are tailored to preventing us from becoming victims of crime. We do things like lock our doors, watch where we walk at night, or avoid walking alone. We take these actions because at some level we are afraid of the possibility of being a victim of crime. Although we may not consciously think about it, these routines may be influenced by a variety of factors. What factors might make some individuals more afraid than others?

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