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Regression

This applet lets you estimate the regression line and to guess the value of Pearson's correlation.

Concepts: central tendency, mean, median, skew, least squares.

Fitness of regression

This applet allows you to examine the effects of the reliability of X and Y on a number of the components of the regression analysis.

concepts: reliability, standard error of estimate, slope, correlation.

Median,Mean

This applet demonstrates basic properties of the mean and median including .

Concepts: central tendency, mean, median, skew, least squares.

Sampling distribution

This applet estimates and plots the sampling distribution of various statistics. You specify the population distribution, sample size, and statistic. An animated sample from the population is shown and the statistic is plotted. This can be repeated to estimate the sampling distribution.

Concepts: sampling distribution, standard deviation, standard error, central limit theorem, mean, median, efficiency, fluctuation, skew, normal distribution

Confidence interval

This applet simulates sampling from a population with a mean of 50 and a standard deviation of 10 and estimates the confidence interval.

Concepts: confidence interval, mean, standard deviation.

Normal Approximation to the Binomial Distribution

This applet allows you to approximate a binomial distribution by a normal distribution.

Concepts: binomial distribution, normal distribution, central limit theorem, correction for continuity.

Confidence Interval on a Proportion

This applet shows the effect of violating the assumption that the sampling distribution of p is normal

Concepts: binomial distribution, normal distribution, central limit theorem, confidence interval.

Components of r

This applet allows you to show a scatterplot of data from a bivariate distribution in which the relationship between the two variables is linear.

Concepts: Correlation, slope, standard error of the estimate, variance, restriction of range, proportion of variance explained.

Restriction of Range

This applet showa taht the the range of X can be manipulated to investigate its effect on Pearson's r and other aspects of the relationship between X and Y

Concepts: Correlation, restriction of range, slope, standard error of estimate.

Repeated measures

This applet lets you investigate differences between correlated and independent t tests.

Concepts: t test, within-subject variable, between-subject variable, power, repeated measures.

Chi Square Test

This applet does the sampling and tests the significance of deviations from these two distributions.

Concepts: goodness of fit, chi square, normal distribution, uniform distribution.

2 x 2 Contingency Tables

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.

Concepts: chi square, correction for continuity, normal approximation.

Histogram,cross-validation

This applet demonstrates how a histogram is affected by bin width and starting point of first bin. Illustrates cross-validation criterion for assessing histograms.

concepts: histogram, bin width, cross validation, density estimation.

Exponential logarithmic functions

This applet shows how transformations affect the relationship between two variables.
L'applet permet de faitre des transformations logarithimiques,racine, carré, d'une régression linéaire.

concepts: histogram, bin width, cross validation, density estimation.

Robustness of t-test and ANOVA

This applet simulates t-test/ANOVA with normality and homogeneity of variance assumptions violated

Concepts: Assumptions, robustness, type I error rate, homogeneity of variance, normality.

One-way ANOVA

This applet shows partitioning of variance.

Concepts: ANOVA, sums of squares, partitioning variance.

Two-way ANOVA

This applet shows partitioning of variance.

Concepts: ANOVA, sums of squares, partitioning variance, interaction.L'applet permet de voir ce qui se passe dans l'analyse de la variance à deux facteurs(ANOVA).