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  • This presentation is a part of a series of lessons on the Analysis of Categorical Data. This lecture covers the following: the poisson log-linear model, poisson regression, estimated rate ratio, and negative binomial distribution.

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  • This is a graduate level introduction to statistics including topics such as probabilty/sampling distributions, confidence intervals, hypothesis testing, ANOVA, and regression.  Perfect for students and teachers wanting to learn/acquire materials for this topic.

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  • The objective of this course is to learn and apply statistical methods for the analysis of data that have been observed over time.  Our challenge in this course is to account for the correlation between measurements that are close in time. Perfect for students and teachers wanting to learn/acquire materials for this topic.

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  • A collection of Java applets and simulations covering a range of topics (descriptive statistics, confidence intervals, regression, effect size, ANOVA, etc.).

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  • How can we accurately model the unpredictable world around us? How can we reason precisely about randomness? This course will guide you through the most important and enjoyable ideas in probability to help you cultivate a more quantitative worldview.

    By the end of this course, you’ll master the fundamentals of probability and random variables, and you’ll apply them to a wide array of problems, from games and sports to economics and science.  This course includes 62 interactive quizzes and more than 400 probabilty-based problems with solutions.  Access to this course requires users to sign up for a free account.

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  • This site offers separate webpages about statistical topics relevant to those studying psychology such as research design, representing data with graphs, hypothesis testing, and many more elementary statistics concepts.  Homework problems are provided for each section.

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  • Approximating a normal distribution with a binomial distribution

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  • A joke to aid in discussing probability density functions for continuous random variables.  The joke was written in 2016 by Judah Lesser an AP statistics student from El Paso, Texas.

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  • A joke that can be used in distinguishing the difference between the probability mass function (pmf) for discrete variables and the probability density function (pdf) for continuous variables. The idea for the joke came in 2016 from Judah Lesser, an AP Statistics student from El Paso Texas.
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  • A cartoon for use in teaching about the Normal distribution. The cartoon was drawn by Australian epidemiologist Matthew Freeman of the Public Health Information Development Unit at the University of Adelaide. It is free for use on course websites or in the classroom provided author acknowledgement is given (e.g. leave copyright statement on the image). Commercial uses should contact the copyright holder. The cartoon was also published under the title "A visual comparison of normal and paranormal distributions" in the Journal of Epidemiology and Community Health (2006) 60(1):6
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