Gelman А., Nolan D. Teaching Statistics: A Bag of Tricks

2nd Edition. — Oxford University Press, 2017. — 421 p.Students in the sciences, economics, social sciences, and medicine take an introductory statistics course. And yet statistics can be notoriously difficult for instructors to teach and for students to learn. To help overcome these challenges, Gelman and Nolan have put together this fascinating and thought-provoking book. Based on years of teaching experience the book provides a wealth of demonstrations, activities, examples, and projects that involve active student participation.
Part I of the book presents a large selection of activities for introductory statistics courses and has chapters such as 'First week of class'― with exercises to break the ice and get students talking; then descriptive statistics, graphics, linear regression, data collection (sampling and experimentation), probability, inference, and statistical communication.
Part II gives tips on what works and what doesn't, how to set up effective demonstrations, how to encourage students to participate in class and to work effectively in group projects. Course plans for introductory statistics, statistics for social scientists, and communication and graphics are provided.
Part III presents material for more advanced courses on topics such as decision theory, Bayesian statistics, sampling, and data science.Introductory probability and statistics
First week of class
Descriptive statistics
Statistical graphics
Linear regression and correlation
Data collection
Statistical literacy and the news media
Probability
Statistical inference
Multiple regression and nonlinear models
Lying with statistics
Putting it all together
How to do it
Structuring an introductory statistics course
Teaching statistics to social scientists
Statistics diaries
A course in statistical communication and graphics
More advanced courses
Decision theory and Bayesian statistics
Student activities in survey sampling
Problems and projects in probability
Directed projects in a mathematical statistics course
Statistical thinking in a data science course