These tools are provided free for students of statistics (and others). These tools are based on the ActivStats statistics e-book.

The first three demonstrate fundamental principles important to statistics.

The four online tables are a convenient way to look up critical values from those distributions.

The final four tools provide randomization-based ways to perform inference that can be used to supplement classical frequentest inference methods—or even to replace them.

These tools provide built-in datasets, but can also be used with any tab-delimited text data file for which the first row holds variable names.

**Contact Us to submit an issue to the Data Desk Technical Support Team**.

## Probability Visualizations

### The Law of Large Numbers

This is a simulation of the Law of Large Numbers

### Random Quantitative Generator

This tool is the continuous version of the Law of Large Numbers tool.

### Central Limit Theorem

This tool demonstrates the Central Limit Theorem. In operation, it works much like the Random Quantitative Generator tool (which you might want to look at first).

## Tables

### Normal Table

This is an interactive Normal probability table, similar to those found in the back of most statistics textbooks.

### t Table

This is an interactive Student’s t probability table, similar to those found in the back of most statistic textbooks.

### Chi Square Table

This is an interactive Chi square probability table, similar to those found in the back of most statistic textbooks.

### F Table

This is an interactive F probability table, similar to those found in the back of most statistic textbooks.

## Simple Samples

### Simple Sample

This tool provides a way to draw a simple random sample from a set of data.

### Regression Simple Sample

The regression simple sample tool performs repeated samples (without replacement) from the data provided, computes the least squares regression slope relating two variables, and accumulates the resulting slopes.

## Randomization Tests

### Binary Randomization Tests

Take two variables, one binary variable X and one binary Y.

### Quantitative Randomization Tests

Take two variables, one binary variable X and one quantitative Y.

## Bootstraps

### Mean Bootstrap

The bootstrap mean tool finds a bootstrapped confidence interval for the mean of any variable.

### Regression Bootstrap

The regression bootstrap tool performs a bootstrapped estimate of a confidence interval for the least squares regression slope relating two variables.