Univariate Distributions

  • 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 site describes in detail 5 different types of random sampling, giving examples, definitions, and procedures.
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  • This worksheet gives students 4 excercises in designing a case study. Each exercise presents a difference scenario and asks a series of questions about study design.
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  • This site discusses survey questionnaires and interviews, provides links to detailed descriptions and pros and cons of each, and describes how to conduct them.
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  • This site takes the user through the steps and decisions necessary when designing a survey. Pros and cons for each method are outlined and other issues in survey design are presented.
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  • This site lists definitions of key terms related to experimental design and ANOVA, including factorial, blocking, interaction, and others. This site is part of the "Statistics Glossary" for the STEPS project (STatistical Education through Problem Solving).
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  • This site explains the 2x2 factorial experimental design, it's components, and it's effects. Graphs illustrate the concepts discussed.
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  • This applet simulates finding confidence intervals for the mean of a normal random variable. A sample of size 20 is generated from a standard normal random variable. The blue marks represent the sample data. The sample mean X and sample standard deviation s are found and used to calculate the confidence interval. The black intervals are the confidence intervals which include the true mean 0, and the red intervals are those which exclude 0. This applet needs to be resized for optimal viewing.
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  • This applet demonstrates probability as the area under the normal and the standard normal curves. Students can manipulate mean, standard deviation, and lower and upper bounds to find probabilities.
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  • This website is a collection of analysis tools commonly used in statistics and mathematics. These tools are divided into 7 categories: 1) Summarizing Data 2)Computational Probability 3)Requirements for most tests and computations 4) One population and one variable 5)One population and two or more variables 6)Two or three populations and one variable 7) Several populations and one or more variables

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