Data Collection

  • This chapter of the NIST Engineering Statistics handbook "describes the terms, models and techniques used to evaluate and predict product reliability." It contains an introduction, discussions on the assumptions, and sections on reliability data collection and analysis.
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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 is the Statistical Consulting Service Web Resources page for York University. It includes lists of statistical and statistical graphics resources, SAS information guides, online statistical computing applets, and a bibliography of articles for the statistics user.

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  • This site contains data sets to help teach a Chance course and help students understand issues that may not be found in a standard statistics text. Topics covered include: mean, median, random walks, regression, correlation, and more.
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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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  • 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 pdf file gives definitions for average, standard deviation, and relative standard deviation, and works through a short problem as an example.
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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 applet plots the survival function (1-F(t)) of the exponential distribution against the empirical survival function. The empirical survival function is one minus the empirical distribution function.

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