Materials

This is a list of additional course materials. I will post new files and website links as we progress through the course. There is a list of recent files on the homepage which will update so you can easily see if what new links I've posted.

An Intuitive Explanation of Bayes' Theorem

Arthur Benjamin: Teach statistics before calculus!

Bad Science — A good site for learning statistics through practical examples.

Causation — Correlation is not Causation

Central Limit Theorem — Demonstration of CLT

Central Limit Theorem — Another fun way to demonstrate the CLT is with fair dice. Simply have someone roll 1 die 50 times noting their results after each roll. When they graph this the distribution will be very flat. Then give them 2 die and have them roll them both at the same time 50 times (averaging the results each run). Finally, give them 5 die and repeat. You will see the distribution become more and more normal as the sample size, n, increases.

Confidence Intervals

Data Analysts Captivated by R’s Power — Business Computing

Devs Love Bacon: Everything you need to know about Machine Learning in 30 minutes or less — Bayes rule

For Today’s Graduate, Just One Word: Statistics

Galton Board — Bernoulli-Binomial-Normal (CLT)

Hans Rosling: Religions and babies — A nice video about data analysis.

Higgs: is it one-sided or two-sided? — p-value explanation

How Bayes’ Rule Can Make You A Better Thinker

How to do stuff in R. two minutes or less. — Videos about R

Hypothesis Testing — Demonstration of HT

Hypothesis tests, p-value - Statistics Help

Inferential Statistics: A Different Approach

Inferential statistics and other animals — the difference between descriptive stats and inferential stats

Information is Beautiful — Visualizing Data.

introducing R to a non-programmer in one hour

Introduction to Minitab — Software

MacEwan — good teaching material site

Modes, Medians and Means: A Unifying Perspective

Monty Hall Simulations — a good reference for Project 2

Probabilities for the Normal Distribution

Quick-R — accessing the power of R

Sampling Distribution Simulation — Demonstration of Sampling Distribution

Sampling Error Isn’t — A good explanation of sampling variation

Significance — how to interpret the significance of hypothesis testing

Significance — a good post about statistical significance and p-value

Statistics Done Wrong — p value and statistical significance

statistics for corpus linguists

statsteachR — statsTeachR is an open-access, online repository of modular lesson plans, a.k.a. "modules", for teaching statistics using R at the undergraduate and graduate level. Each module focuses on teaching a specific statistical concept. The modules range from introductory lessons in statistics and statistical computing to more advanced topics in statistics and biostatistics.

Teach Data Science — a good book on data science with R

Teaching least squares

The age of big data

The Data and Story Library — data from a wide variety of topics so that statistics teachers can find real-world examples that will be interesting to their students.

The Higgs boson: 5-sigma and the concept of p-values — p-value

The Monty Hall Problem — a fantastic explanation of the Monty Hall Problem

The Soul of Statistics — Joseph Blitzstein: "The Soul of Statistics" | Harvard Thinks Big

two-sample

Uncertainty, luck and control — a good post about the probability

Understanding Uncertainty — The site tries to make sense of chance, risk, luck, uncertainty and probability.

Variation - Why statistical methods are needed

Visualizing Bayes’ theorem — blog post

Wainer’s website for his intro stat course

Wealth Inequality in America

What is data science? — an article

What is R