Visualize and run a permutation test comparing two samples with a quantitative response.

Explore how mean and standard deviation change the shape and find percentiles (critical values) or probabilities.

Find the probability for the number of successes in n Bernoulli trials. Explore how the distribution depends on n and p.

Find summary statistics and construct inter-active histograms, boxplots, dotplots or stem & leaf plots. For **one **or** several **samples.

Coming soon ...

Explore how the degrees of freedom effect the shape and find percentiles, probabilities and P-values

Coming soon ...

Confidence interval and significance test for the difference of two proportions. Independent & dependent samples.

Explore how the shape depends on the two sets of degrees of freedom. Find and visualize percentiles and probabilities.

Randomly generate scatterplots to guess the correlation coefficient *r*. Optionally, display the regression line. How do your guesses correlate with the actual values?

For **continuous** variables. Choose from many different population distributions (or built your own) and explore the sampling distribution.

Generate random numbers or flips of a (biased) coin. Keep track of generated numbers with a bar chart.

Construct frequency and contingency tables and bar graphs to explore distributions of categorical variables. For **one **or** two** variables.

Plot a simple time series and add a smooth or linear trend.

Supply your own data to construct an interactive scatterplot and superimpose a regression line. Obtain the intercept, slope, r and r-squared. Dispaly and analyze residuals. Make predictions or obtain confidence or prediction intervals.

Create scatterplots from scratch by clicking in an empty plot and creating points. Investigate the effect of outliers on the regression line. Simulate linear or non-linear relationships.

Find confidence intervals and test hypo-theses about a population proportion. Visualize the interval or P-value.

Construct 2x2 contingency tables, obtain conditional proportions and get a bar graph. Find the **difference** or **ratio** of proportions. Built the sampling distribution via resampling.

Explore how the shape of the Poisson Distribution depends on λ and find probabilities of various kinds

Analysis of Variance for one factor, including multiple comparisons of means (Tukey, Dunnett, Bonferroni). (soon)

Test for independence, homogeneity or goodness of fit in contingency tables. Analyze observed & expected counts and residuals.

Visualize and run a permutation test for testing independence in a contingency table using Pearson's Chi-squared statistic.

See how the sampling distribution builds up with repeated sampling and explore how its shape depends on n and p.

Visualize and run Fisher's exact test for

2 x 2 contingency tables.

For **discrete** variables. Define your own discrete distribution (such as uniform or skewed) and explore the sampling distribution.

Explore how the shape depends on the degrees of freedom. Find and visualize percentiles and probabilities.

Explore the relationship between the mean and median for data coming from a variety of distributions, or enter your own data.

Construct interactive scatterplots to explore the relationship between two quantitative variables while accounting for a third (categorical or quantitative) grouping variable.

Create the bootstrap distribution of the mean, median or standard deviation and find the bootstrap confidence interval.

Confidence interval and significance test for the difference of two means. Independent & dependent samples.

Explore probabilities of Type I and Type II errors and connections to sample size, significance level and true parameter value.

Find confidence intervals and test hypo-theses about a population mean. Visualize the interval or P-value.

What does 95% confidence mean? What affects the width of an interval? Visualize with intervals for proportions or means.

STATISTICS

THE ART & SCIENCE OF LEARNING FROM DATA

AGRESTI · FRANKLIN · KLINGENBERG

Construct interactive scatterplots, hover over points, move them around or overlay a smooth trend line. Find the correlation coefficient *r*. Built the sampling distribution of *r* via bootstrapping or permutation, one resample at a time.