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  • This part of the NIST Engineering Statistics Handbook contains case studies for Exploratory Data Analysis. Some of the topics include normal and uniform random numbers, reliability using airplane glass failure times, and analysis of primary factors using ceramic strength.
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  • This Electronic Statistics Textbook offers training in the understanding and application of statistics ... and covers a wide variety of applications, including laboratory research (biomedical, agricultural, etc.), business statistics and forecasting, social science statistics and survey research, data mining, engineering and quality control applications, and many others. Quoted from the index page of the text.
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  • A useful site for instructors to learn how to create and incorporate guided notes into their classroom.
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  • This lesson deals with the statistics of political polls and ideas like sampling, bias, graphing, and measures of location. As quoted on the site, "Upon completing this lesson, students will be able to identify and differentiate between types of political samples, as well as select and use statistical and visual representations to describe a list of data. Furthermore, students will be able to identify sources of bias in samples and find ways of reducing and eliminating sampling bias." A link to a related worksheet is included.
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  • The Marble Game is a "concept model" demonstrating how a binomial distribution evolves from the occurence of a large number of dichotomous events. The more events (marble bounces) that occur, the smoother the distribution becomes.
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  • This is an exercise in interpreting data that is generated by a phenomenon that causes the data to become biased. You are presented with the end product of this series of events. The craters occur in size classes that are color-coded. After generating the series of impacts, it becomes your assigned task to figure out how many impact craters correspond to each of the size class categories.
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  • This website contains more real analysis, general topology and measure theory than actual probability. It is more about the foundations of probability theory, than probability itself. In particular, it is a very suitable resource for anyone wishing to study the Lebesgue integral. These tutorials are designed as a set of simple exercises, leading gradually to the establishment of deeper results. Proved Theorems, as well as clear Definitions are spelt out for future reference. These tutorials do not contain any formal proof: instead, they will offer you the means of proving everything yourself. However, for those who need more help, Solutions to exercises are provided, and can be downloaded.
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  • This Java applet tutorial prompts the user to input the components of a hypothesis test for the mean. Hints are provided whenever the user enters an incorrect value. Once the steps are completed and the user has chosen the correct conclusion for accepting or rejecting the null hypothesis, a statement summarizing the conclusion is displayed. The applet is supported by an explanation of the steps in hypothesis testing and a description of one-tailed and two-tailed tests.
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  • This online, interactive lesson on random samples provides examples, exercises, and applets concerning sample mean, law of large numbers, sample variance, partial sums, central limit theorem, special properties of normal samples, order statistics, and sample covariance and correlation.
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  • This online, interactive lesson on point estimation provides examples, exercises, and applets concerning estimators, method of moments, maximum likelihood, Bayes estimators, best unbiased estimators, and sufficient, complete and ancillary statistics.
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