Linear Models

  • This page will calculate the intercorrelations (r) for any number of variables (V1, V2, V3, etc.) and for any number of observations per variable.

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  • This resource defines a pie chart. It also allows the user to input values to create their own graphs. The user has control over the title, up to 15 slices, the color of each slice, and can choose a 3-D option.

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  • The applet in this section allows for simple data analysis of univariate data. Users can either generate normal or uniform data for k samples or copy and paste data from another source to a text box. A univariate analysis is performed for all k samples. A two-sample t-test (Pooled and Satterthwaite) is performed for k = 2. An ANOVA test is performed for k > 2. This page was formerly located at http://www.stat.vt.edu/~sundar/java/applets/Data.html
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  • In this activity, students work in groups to provide practical interpretations of graphs, considering shape, center, and spread. Each group posts their interpretation for one graph and critiques other groups' interpretations on other graphs. Students examine key aspects (shape, spread, location, etc) of histograms and stem plots to develop the ability to interpret graphics. This activity gets the students up and out of their seats and working together. It is a good activity for early in a term. The Gallery Walk idea can be adapted for different sized classes but this activity has been designed for classes up to 65 students.
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  • This one-page document gives some helpful tips about the first day of class. It gives short advice on creating a first impression, establishing rapport, clarifying expectations, collecting information and building excitement.
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  • This site lists definitions of key terms related to experimental design and ANOVA, including factorial, blocking, interaction, and others. This site is part of the "Statistics Glossary" for the STEPS project (STatistical Education through Problem Solving).
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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 tutorial takes the learner step-by-step in applying descriptive and inferential statistics using a real world situation.
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  • (Uses JAVA)  Some basic statistical analysis tools that allow the user to input their own data or use the pre-existing data and perform the desired test (e.g ANOVA, Descriptive, t-test, chi-square, correlation and regression).

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