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  • Textbook-like example showing the independent t-test. Gives a nice way for students to think through the problem and interpret results.
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  • 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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  • 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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  • 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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  • This tutorial on the Two Sample t test includes its definition, assumptions, hypotheses, and results as well as tests for equal variance and graphical comparisons. An example using output from the WINKS software is given, but those without the software can still use the tutorial. An exercise is given at the end that can be done with any statistical software package.
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