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Statistical Topic

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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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  • The applets in this section of Statistical Java address Power. Users can perform one or two tailed tests for proportions or means for one or two samples. Set the parameters and drag the mouse across the graph to see how effect size affects power. An article and an alternative source for this applet can be found at http://www.amstat.org/publications/jse/v11n3/java/power/ This page was formerly located at http://www.stat.vt.edu/~sundar/java/applets/Power.html
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  • The applets in this section of Statistical Java allow you to see how levels of confidence are achieved through repeated sampling. The confidence intervals are related to the probability of successes in a Binomial experiment. The main page gives the equation for finding confidence intervals and describes the parameters (p, n, alpha). Each applet allows you to change a different parameter and simulate sampling to demonstrate the long run proportion of intervals that contain the true probability of success. The applets are available from a pull-down menu at the bottom of the page. This page was formerly located at http://www.stat.vt.edu/~sundar/java/applets/CI.html
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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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  • 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 comprehensive collection of calculators provides users with resources for everything from introductory statistics to advanced statistical methods. Users can search by the following categories: Dictionaries, Courses with Calculators and Applets, Courses All Inclusive, and Statistics A-Z. Users can also search by the following statistical specialties: Agriculture, ANOVA, ANCOVA, Bayesian, Economics, Employment, Health, Information & Library Science, Psychology, Reliability Modeling, Research: Marketing and Opinion, Sampling Analysis, and SAS.
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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 applet demonstrates probability as the area under the normal and the standard normal curves. Students can manipulate mean, standard deviation, and lower and upper bounds to find probabilities.
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