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Article originally posted on **Data Science Central.** Visit **Data Science Central**

Online Statistics Education: A Multimedia Course of Study. Project Leader: David M. Lane, Rice University.

**Content**:

- Introduction
- Graphing Distributions
- Summarizing Distributions
- Describing Bivariate Data
- Probability
- Research Design
- Normal Distributions
- Advanced Graphs
- Sampling Distributions
- Estimation
- Logic of Hypothesis Testing
- Testing Means
- Power
- Regression
- ANOVA
- Transformations
- Chi Square
- Distribution Free Tests
- Effect Size
- Case Studies
- Calculators
- Glossary

*Guess what the correlation is: see here*

The (free) PDF version (660 pages) is available here.The online book also features various calculators (Gaussian distributions etc.) as well as the following simulations:

- Introduction: Sampling, Measurement
- Graphing Distributions: Box Plot
- Summarizing Distributions: Balance Scale, Absolute Difference, Squared Differences, Mean and Median,Variability Demo, Estimating Variance , Comparing Distributions
- Describing Bivariate Data: Guessing Correlations, Restriction of Range
- Probability: Conditional Probability, Gamblers Fallacy, Birthday, Binomial, Bayes’ Theorem, Monty Hall Problem
- Normal Distributions: Varieties of Normal Distributions, Normal Approximation
- Sampling Distributions: Basic Demo, Sample Size Demo, Sampling Distributions, Central Limit Theorem
- Estimation: Confidence Interval
- Logic of Hypothesis Testing (none): Testing Means, t Distribution, Robustness , Correlated t Test
- Power: Power 1, Power 2
- Prediction: Linear Fit

ANOVA: One-Way, Power of Within-Subjects Designs - Chi Square: 2 x 2 Table, Testing Distributions

This resource is accessible here.

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- Central Limit Theorem and Statistical Testing: Beyond the Basics
- Free book: Applied Stochastic Processes

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