Teaching Statistics: A Bag of Tricks
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.
What people are saying - Write a review
We haven't found any reviews in the usual places.
Other editions - View all
5min activities Andrew Gelman answer ask the students average Bayesian Bayesian statistics bias biased binomial binomial distribution blackboard cards Chapter class discussion classroom coin flips concepts confidence intervals consider correlation data analysis data collection demonstration described in Section display due at beginning error estimate exam scores example experiment give grade graph graphics guess handouts height helicopter histogram homework assignments ideas instructor interesting introductory statistics jitts lecture linear linear regression logarithmic lurking variable Markov chain mathematical mean methods minutes newspaper article normal distribution November 25 paper patients plot population present probability problem questions random digits random numbers Readings before class regression San Francisco Examiner scatterplots semester sequence simulation Special guest star standard deviation statistical literacy statistically significant statistics class statistics course survey survey sampling teaching topic typically visualization write