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Statistical Topic

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  • This collection of applets simulate many different statistical concepts such as: distributions, correlation, hypothesis testing, regression, and ANOVA.
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  • This section in the Engineering Statistics Handbook takes a data set and walks the user through analysis and experimental design based on the data.
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  • The GAISE project was funded by a Strategic Initiative Grant from ASA in 2003 to develop ASA-endorsed guidelines for assessment and instruction in statistics in the K-12 curriculum and for the introductory college statistics course.
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  • A computer intensive introductory course for graduate students. A veritable online course with Powerpoint and Excel downloadable files for viewing. Also provides related outside links for further investigation on related topics.
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  • A collection of links to video workshops for students in mathematics. Includes many topics from statistics to math and science to algebra.
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  • The goal of this lesson is to introduce the concepts of mean, median and mode and to develop understanding and familiarity with these ideas. The activity lets students explore mean and median in an efficient way and the discussion helps them to formalize their knowledge of measures of center.
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  • Develops the idea of the transition matrix and what it can tell you.
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  • This lesson on observational studies discusses the nature of such studies, the relationships between various data sets, and regression. Graphs illustrate the relationships, and exercises at the end test the user's comprehension and understanding. It is taken from the online textbook for West. Mich. Univ. online introductory stats course.
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  • The function of this site is to collect, compile, analyse, abstract and publish statistical information relating to the commercial, industrial, financial, social, economic and general activities and condition of the people.
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  • A good resource for problems in statistics in engineering. Contains some applets, and good textual examples related to engineering. Some topics include Monte Carlo method, Central Limit Theorem, Risk, Logistic Regression, Generalized Linear .Models, and Confidence.
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