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  • The applet in this section allows you to see how the T distribution is related to the Standard Normal distribution by calculating probabilities. The T distribution is primarily used to make inferences on a Normal mean when the variance is unknown. If the variance is known inference on the mean can be done using the Standard Normal. The user has a choice of three different probability expressions, then can change the degrees of freedom and the limits of probability. This page was formerly located at http://www.stat.vt.edu/~sundar/java/applets/TNormal.html
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  • In this demonstration a scatterplot is displayed and you draw in a regression line by hand. You can then compare your line to the best least squares fit. You can also try to guess the value of Pearson's correlation coefficient.
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  • This applet shows how the correlation between two variables is affected by the range of the variable plotted on the X-axis.
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  • This applet demonstrates that even a "small" effect can be important under some circumstances. Applicants from two groups apply for a job. The user manipulates the mean and the cut-off score in order to see the effects the small changes has on the number of people hired in each group. The effects on the proportion of hired applicants from each group are displayed.(Requires a browser that supports Java).
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  • The applet allows users to sample from a normal distribution or from a uniform distribution. It shows the expected values and the observed values and computes the deviation. Then, a chi-square test shows if the deviations are significant for both the normal and uniform distributions.
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  • This applet simulates experiments using 2 x 2 contingency tables. You specify the population proportions and the sample size and examine the effects on the probability of rejecting the null hypothesis.
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  • This applet demonstrates how the reliability of X and Y affect various aspects of the regression of Y on X.
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  • This applet demonstrates how a histogram is affected by bin width and starting point of first bin. It also illustrates cross-validation criterion for assessing histograms.
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  • This is a simulation illustrating the regression toward the mean phenomenon.
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  • This simulation shows recorded response times on a simple motor task under two conditions. Various statistics and graphs used to compare the distributions are presented.
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