Videos
Overview
Statistics in Action
Chapter 1
Introduction to Data
Chapter 2
Probability
Chapter 3
Distributions
Chapter 4
Foundations for Inference
Chapter 5
Inference for Numerical Data
Chapter 6
Inference for Categorical Data
Chapter 7
Introduction to linear regression
Chapter 8
Multiple and logistic regression
Casio fx‑9750GII
TI83/84 Plus

Watch and learn. OpenIntro is releasing videos introducing book sections in 38 minute videos. Check out our initial offering and come back for new releases. Scripts for many of our videos Provide Feedback or Suggest a Helpful Video Help us make better videos and share more resources 
Learn about how data and statistics are crucial to research, government, business, and industry.
Visualize world history through health and wealth with Hans Rosling
Hans Rosling brings life to global health statistics
Steven Levitt explores the value of child car seats (disclaimers at the end)
Susan Murphy uses statistics to treat chronic illnesses, such as alcoholism
David Lobell analyzes all sorts of data to better understand agriculture
Don Knuth helps his univerity's basketball coach make better decisions (1959)
NY Times: As 'Normal' as Rabbits' Weights and Dragons' Wings
A special thank you to the following people who have suggested one or more of the videos above: Nick Horton, Albert Kim. 
Learn how to summarize data using graphics and statistics, and learn scientifically sound techniques for collecting data. 1.1 Case study: using stents to prevent strokes
1.2 Data basics
1.3 Overview of data collection principles
1.4 Observational studies and sampling strategies
1.5 Experiments
1.6 Examining numerical data
1.7 Considering categorical data
1.8 Case study: gender discrimination

Learn scientificallysound techniques for collecting data. 1.1 Case study: using stents to prevent strokes
1.2 Data basics
1.3 Overview of data collection principles
1.4 Observational studies and sampling strategies
1.5 Experiments

Learn how to summarize data using graphics and statistics. 2.1 & 2.2 Examining numerical data
2.3 Considering categorical data
2.4 Case study: gender discrimination

Probability forms a foundation for understanding nuances about data and the methods we use to analyze data.
2.1 Defining probability
2.2 Tree Diagrams (sub section)
Would you take this bet?

A solid grasp of the normal distribution plays a pivotal role in applying commonly used statistical techniques. Familiarity with additional distributions provides a foundation that will be useful in later courses. 3.1 Normal distribution
3.2 Evaluating the normal distribution
3.4 Binomial distribution

Learn about the principles of inference that are used throughout much of statistics. 4.1 Variability in estimates
4.2 Confidence intervals
4.3 Hypothesis testing
4.X Why do we use 0.05 as a significance level?
4.4 Central Limit Theorem
4.5 Inference for Other Estimators
4.X Sample size and power

Inference for numerical data, such as for a single mean, the mean of paired data, or the difference of two means.
5.1 Part 1  tdistribution
5.1 Part 2  Inference for a mean
5.2 Inference for paired data
5.3 Difference of two independent means
5.4 Power calculations for difference of two means
5.5 Part 1  ANOVA Intro
5.5 Part 2  Conditions for ANOVA
5.5 Part 3  Multiple comparisons

Inference for proportions, goodness of fit, and 2way tables.
6.1 + 6.2 Inference for proportions
6.3 Testing for goodness of fit using chisquare
6.4 Homogeneity and independence in twoway tables

Linear regression provides substantial insights that are most commonly understood through visual representations. This material provides an introduction to linear regression concepts, methods, and inference. 7.1 Line fitting, residuals, and correlation
7.2 Fitting a line by least squares regression
7.3 Types of outliers in linear regression
7.4 Inference for linear regression

Multiple and logistic regression are the most powerful methods introduced in OpenIntro Statistics. These methods are key elements of any statistician's toolkit. 8.1 Introduction to multiple regression
8.2 Model selection
8.3 Checking model assumptions using graphs
8.4 Logistic regression

The Casio fx9750GII graphing calculator is comparable to a TI83 or TI84 in features but costs half the price, typically coming in at These videos were made to help students and teachers who are interested in using this intuitive yet affordable calculator. 1Variable statistics & box plot
Compute the binomial coefficient (n choose x)
Compute the binomial formula
Normal distribution calculations
1Prop. confidence intervals & hypothesis testing
How to plot the pvalue for a test
2Prop. confidence intervals & hypothesis testing
1Sample confidence intervals & hypothesis testing (1 mean)
2Sample confidence intervals & hypothesis testing (2 means)
Chisquare goodnessoffit test
Chisquare test for 2way tables
Chisquare tail area calculation
Calculating regression summary statistics
Conducting a ttest in the regression context

The TI83 Plus and TI84 Plus graphing calculators are the most popular graphing calculators, but they are also more expensive than the comparable Casio fx9750GII graphing calculator. Below is a compilation of TI84 calculator videos that we think may be useful to students using this calculator. TI83 instructions are very similar to those of the TI84. Entering data and 1variable statistics
Constructing a box plot
Binomial coefficient
Binomial formula
Binomial cumulative distribution function
Computing tails of the normal distribution with Zscores
Inverse normal distribution calculations
1Proportion hypothesis test
1Proportion confidence interval
2Proportion hypothesis test
2Proportion confidence interval
1Sample hypothesis test (1 mean)
1Sample confidence interval (1 mean)
2Sample hypothesis test (2 means)
2Sample confidence interval (2 means)
Chisquare upper tail area
Chisquare goodnessoffit test
Chisquare test for 2way tables
Calculating regression summary statistics
Conducting a ttest in the regression context
Confidence interval for slope of a regression line

Videos
Overview
Statistics in Action
Chapter 1
Introduction to Data
Chapter 2
Probability
Chapter 3
Distributions
Chapter 4
Foundations for Inference
Chapter 5
Inference for Numerical Data
Chapter 6
Inference for Categorical Data
Chapter 7
Introduction to linear regression
Chapter 8
Multiple and logistic regression
Casio fx‑9750GII
TI83/84 Plus
