# STATISTICAL TOPICS

## BASICS

**Intro to Statistics**This page introduces the main concepts in statistics: descriptive statistics to summarize a data set, inferential statistics to answer questions about populations based on sample data, and a bit about three other approaches to statistics.

## PROBABILITY

**Intro to probability**This page talks about the basics of how we compute probabilities. This includes the probabilities of combinations of two events: (1) the probability of event A

**or**B; (2) the probabilty of event A

**and**B. It also briefly describes Bayes' Theorem. Lots of examples are provided.

**The Binomial distribution**These pages explain the scenario that the binomial probability distribuition models, the assumptions required for using the equation, and give step-by-step examples of how to use the equation.

## CONFIDENCE INTERVALS

## STATISTICAL TESTS

**One Sample T-test**This page describes how the one sample t-test can be used to test hypotheses about a population mean: including the conceptual model, how the t-distribution is used, one-tailed or two-tailed tests, and several example calculations.

**Two Sample T-test**This page describes how the two sample t-test can be used to test for the equality of pair of population means: including the conceptual model, how the t-distribution is used, one-tailed or two-tailed tests, and several example calculations.

**Variance Ratio F-test**This page describes how the two sample t-test can be used to test for the equality of pair of population variances: including the conceptual model, how the F-distribution is used, one-tailed or two-tailed tests, and several example calculations.

## ANOVA and CORRELATION

## OTHER TOPICS

**Type I and II errors**This page explains the two main types of statistical errors: type I (where we reject a true null hypothesis) and type II (where we accept a false null hypothesis. The metaphor of the US justice system is used to make this clear.

# Connect with StatsExamples here

This information is intended for the greater good; please use statistics responsibly.