Statistical Inference & Techniques

  • Gives very detailed explanation of t-tests (confidence intervals, one-sample, two sample independent, two sample paired, pooled and unpooled variances). Discusses the assumptions that are made for each type of t-test. This topic is part of an online textbook.
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  • Gives a basic explanation with diagrams of the one and two-tailed t-tests.
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  • Gives four practice problems on the t-test. Gives both the data sets and the mean and standard deviations if you did not want to compute them. Requires students to interpret and reason through some of their answers.
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  • This applet demonstrates the partitioning of sums of squares in analysis of variance (ANOVA). It includes some sample values and allows the user to make adjustments, which then shows the new values in the ANOVA table. Also contains an exercise set.

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  • A computational tool that runs the one-way ANOVA by the user inputing individual data or by copying and pasting a delimitted data set.

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  • Visual ANOVA is a simple little program that lets you put all this theory we've been describing into a simple visual whole. It assumes that you've read the Meanings and Intuitions section and have have understood the the general ideas at least. Even if your understanding of the previous section is incomplete at this time, it is worth playing with Visual ANOVA since that may clear up the big picture of ANOVA for you.

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  • The Against All Odds video series provides an extensive introduction to statistics. It consists of 26 half hour video episodes that include lecturing on statistical topics, animations of statistical topics and video of real world examples. The series is available online or can be purchased on VHS video tape. The statistical material in the series was supervised by Dr. David Moore and accordingly much of the material echos the language used in Moore's textbooks. Topics covered include most topics from an introductory statistics course and slightly more advanced topics such as seasonal variation, blocking of experimental designs and even Chernof faces. The material is very well suited for students in undergraduate statistics classes.
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  • This activity allows users to create and manipulate boxplots for either built-in data or their own data. Discussion, exercise questions, and lesson plans regarding boxplots are linked to the applet.
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  • An explanation of scatter plots, their use, purpose and interpretation. It provides examples of the various relationships described by scatter plots as well as case studies and related techniques.
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  • This activity allows the user to create and manipulate histograms with built-in or user-specified data, and provides links to discussion and exercise questions. The mean and standard deviation of each data set are also calculated and the bin width of each histogram can be changed by the user.
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