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  • This resource gives 3 questions readers should ask when presented with data and why to ask them: Where did the data come from? Have the data been peer-reviewed? How were the data collected? This page also describes why readers should: be skeptical when dealing with comparisons, and be aware of numbers taken out of context.

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  • This applet demonstrates the concept of power. Users select the hypothesized mean, the alternative mean, the sample size, and the number of samples. The applet shows the hypothesized histogram and the alternative histogram. Users then select either the level of significance and set alpha or the rejection region and set the test statistic. The applet then shows the p-value (in red) and power (in green). User can also determine the direction of the test by clicking the inequality sign.

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  • In this applet, we simulate a series of hypothesis of tests for the value of the parameter p in a Bernoulli random variable. Each column of red and green marks represents a sample of 30 observations. "Successes'' are coded by green marks and "failures'' by red marks.

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  • This activity allows the user to experiment with expected values by changing probabilities and payoffs for two people buying stocks, repeating the experiment up to 100 times. There are links to discussion topics and activities related to the applet.

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  • This online, interactive lesson on hypothesis testing provides examples, exercises, and applets which includes tests in the normal model, Bernoulli Model, and two-sample normal model as well as likelihood ratio and goodness of fit tests.

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  • This tutorial exposes students to conducting t-tests in SPSS. This html based tutorial provides extensive screen shots and two example data sets. Topics covered in the tutorial include one sample, paired and independent samples t-tests and conducting transformations (such as a difference) of the data.

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  • Compared to probability calculators, the traditional format of distribution tables has the advantage of showing many values simultaneously and, thus, enables the user to examine and quickly explore ranges of probabilities. This webpage includes a list of distributions and tables, including the standard normal (Z) table, student's t table, chi-square table, and F distribution tables. An animation of the density function and distribution function is shown above each distribution table to demonstrate the effects changing degrees of freedom and significance levels have on the shape of a distribution.

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  • This activity makes use of a campus-based resource to develop a "capstone" project for a survey sampling course. Students work in small groups and use a complex sampling design to estimate the number of new books in the university library given a budget for data collection. They will conduct a pilot study using some of their budget, receive feedback from the instructor, then complete data collection and write a final report.
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  • This activity is an example of Cooperative Learning in Statistics. It uses student's own data to introduce bivariate relationship using hand size to predict height. Students enter their data through a real-time online database. Data from different classes are stored and accumulated in the database. This real-time database approach speeds up the data gathering process and shifts the data entry and cleansing from instructor to engaging students in the process of data production. Key words: Regression, correlation data collection, body measurements
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  • Because surveys are increasingly common in the medical literature, readers need to be able to critically evaluate the survey method. Two questions are fundamental: 1) Who do the respondents represent? 2) What do their answers mean? This lecture example discusses survey sampling terms and aspects of interpreting survey results.
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