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 The Central Limit Theorem The applets in this section of Statistical Java allow you to see how the Central Limit Theorem works. The main page gives the characteristics of five non-normal distributions (Bernoulli, Poisson, Exponential, U-shaped, and Uniform). Users then select one of the distributions and change the sample size to see how the distribution of the sample mean approaches normality. Users can also change the... https://www.causeweb.org/repository/statjava/CLT.html
 Statistical Java This is a collection of applets regarding various topics in statistics. Topics include central limit theorem, probability distributions, hypothesis testing, power, confidence intervals, correlation, control charts, experimental design, data analysis, and regression. Each topic has a description page and links to one or more applets. https://www.causeweb.org/repository/statjava/
 Introductory Statistics: Concepts, Models, and Applications This goal of this resource is to aid in the understanding of the relationship between statistics and the scientific method and how it applies to psychology and the behavioral sciences. The learner will learn how to read and understand the statistics presented in the professional literature and will learn how to calculate and communicate statistical information to others. http://www.psychstat.missouristate.edu/sbk00.htm
 HyperStat Online Textbook This resource contains a broad range of information concerning statistics. It is divided up into eighteen chapters and also includes links to other resources pertaining to statistics. Some of these chapters include: introduction to statistics, describing univariate data, describing bivariate data, introduction to probability, normal distribution, sampling distribution, point estimation,... http://davidmlane.com/hyperstat/
 Tools for Teaching and Assessing Statistical Inference: Sampling SIM This website helps students learn concepts underlying statistical inference, through the simulation software, sampling SIM. This software lets students explore sampling distributions by building population distributions, taking random samples, and exploring the behavior of sampling distributions and confidence intervals. The site includes instructional modules and assessment instruments. http://www.tc.umn.edu/~delma001/stat_tools/
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