Teaching Statistics: A Bag of Tricks 2nd Edition Andrew Gelman 0191088641 9780191088643

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Product details:

• ISBN 10: 0191088641
• ISBN 13: 9780191088643
• Author: Andrew Gelman

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.

Table of contents:

1   Introduction

2   First week of class

3   Descriptive statistics

4   Statistical graphics

5   Linear regression and correlation

6   Data collection

7   Statistical literacy and the news media

8   Probability

9   Statistical inference

10   Multiple regression and nonlinear models

11   Lying with statistics

12   How to do it

13   Structuring an introductory statistics course

14   Teaching statistics to social scientists

16   A course in statistical communication and graphics

17   Decision theory and Bayesian statistics

18   Student activities in survey sampling

19   Problems and projects in probability

20   Directed projects in a mathematical statistics course

21   Statistical thinking in a data science course

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