Lecture Examples

  • 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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  • This tutorial illustrates the basic principles of the Central Limit Theorem and enhances conceptual understand of why the Central Limit Theorem is important to inferential statistics.
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  • This tutorial takes the learner step-by-step in applying descriptive and inferential statistics using a real world situation.
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  • This site addresses mean, median, mode, bar graphs, pie charts, and line graphs. Each topic has multiple examples with related discussion.
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  • This section of the Engineering Statistics Handbook gives the normal probability density function as well as the standard normal distribution equations. Example graphs of the distributions are shown and a justification of the Central Limit Theorem is included.
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