Curriculum

  • This resource defines and explains binomial probability, including examples and exercises for the learner.
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  • This resource is a collection of links for students and teachers of statistics. For students, it includes links to find statistical data. For teachers, it includes links to assist in statistics instruction.
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  • Random is a website devoted to probability, mathematical statistics, and stochastic processes, and is intended for teachers and students of these subjects. The site consists of an integrated set of components that includes expository text, interactive web apps, data sets, biographical sketches, and an object library. 

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  • This one-page document gives advice on how to construct and give exams. It focuses on making exams a positive experience for both instructors and students. It is written by Rich Felder an expert in Engineering education.
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  • This one-page document gives advice on how to handle large classes. Specific items it examines include creating an interactive lecture, handing out of class assignments, and miscellaneous tips. It is written by Rich Felder an expert in Engineering education.
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  • This page of Statistical Java describes 11 different probability distributions including the Binomial, Poisson, Negative Binomial, Geometric, T, Chi-squared, Gamma, Weibull, Log-Normal, Beta, and F. Each distribution has its own applet in which users can manipulate the parameters to see how the distribution changes. The parameters are described on the main page as well as situations that would use each distribution. The equations of the distributions are not given. To select between the different applets you can click on Statistical Theory, Probability Distributions and then the Main Page. At the bottom of this page you can make your applet selection. This page was formerly located at http://www.stat.vt.edu/~sundar/java/applets/

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  • This entry in the online encyclopeida, Wikipedia, describes Markov Chains, their properties, discrete state spaces, and formulas for calculating probabilities using Markov Chains. Links to examples and scientific applications are also included.
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  • This presentation on data analysis addresses observational studies and randomized controlled trials in two different sections. Types of studies are defined and examples of each study is given to emphasize the differences. Factors and variables are also discussed.

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  • This site describes in detail 5 different types of random sampling, giving examples, definitions, and procedures.
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  • This site describes numerous methods of nonprobability sampling, including accidental, haphazard or convenience sampling and the many types of purposive methods.

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