Design of Experiments

  • This chapter of the NIST Engineering Statistics handbook provides information on the proper design of experiments. It contains an introduction, a discussion of assumptions, a description of different design types, a discussion of the analysis of data, and case studies.
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  • This part of the NIST Engineering Statistics handbook contains case studies for the process improvement chapter, which deals with design of experiments.
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  • This reference resource explores the use of clickers, or personal response systems, in the classroom. Main points of discussion include what clickers are, who is using them, what makes them unique, why they are considered significicant, the downsides, and teaching and learning implications.
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  • This site gives an explanation, a definition of and an example using experimental design. Topics include experimentation, control, randomization, and replication.
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  • This site gives an explanation, a definition of, and an example using comparison of two means. Topics include confidence intervals and significance tests, z and t statistics, and pooled t procedures.
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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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  • 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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  • This site briefly defines several different types of sampling methods, contrasts probability and nonprobability sampling, and discusses target population. Part of a tutorial on questionnaire and survey design.
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