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  • This activity guides students through the process of checking the validity of data, performing summary analysis, constructing box plots, and determining whether significant differences exist. The data comes from a study of mineral levels in older adults and is available in Minitab, Excel, SAS, and text formats.
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  • This introductory tutorial for SPSS 10.1 and 11.0 for Windows explains how to enter and summarize data and groups of data and to generate graphs.
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  • This assignment has students investigate whether the risk of having a child with a low birth weight is higher when the mother drinks and smokes during pregnancy. The data set represents a random sample of 1450 births from the state of North Carolina.
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  • A project of the International Association of Statistics Education (IASE). After a first phase of the project led by the outstanding work of Carol Blumberg, where the emphasis was in the development of a series of webpages that will provide users throughout the world with a data bank of international statistical literacy resources for all audiences and in several languages, ISLP is now moving one step ahead. Besides continuing collecting web-based statistical literacy resources from all over the world, ISLP now actively organizes and promotes statistical literacy activities throughout the world and gets actively involved in other worlwide projects. The webpage is a forum where everyone can edit and enter their statistics literacy resources and participate in discussions.
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  • This chapter of the NIST Engineering Statistics handbook "presents techniques for monitoring and controlling processes and signaling when corrective actions are necessary." It contains an introduction to process control, a discussion of acceptance sampling, introductions to control charts and time series modeling, tutorials for background information, and case studies.
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  • This chapter of the NIST Engineering Statistics handbook presents information on the statistical modeling of an engineering process. It contains an introduction, discussion of the assumptions, information about data collection and analysis, a discussion of what can be concluded from different process models, and case studies.
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  • This part of the NIST Engineering Statistics handbook contains case studies for the production process characterization chapter.
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  • This page, part of the NIST Engineering Statistics handbook, contains links to web pages which have tables of values for various distributions.
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  • This page, part of the NIST Engineering Statistics handbook, contains links to web pages describing most of the more commonly used distributions.
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  • This page, part of the NIST Engineering Statistics handbook, describes the Kolmogorov-Smirnov goodness of fit test. It contains a graph of the empirical distribution function with the cumulative distribution function, a definition of the test, the questions it answers, the assumptions that it makes, and links to other goodness of fits tests and a case study.
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