Statistics: Concepts and Controversies » (6th Edition)

The data analysis approach pioneered by David Moore was first introduced in this groundbreaking brief text for liberal arts students. By emphasizing concepts and applications to a wide range of fields (as opposed to formulas and computation) the text has become an influential bestseller, and its emphasis on ideas and data is now generally acknowledged as the most effective way to teach statistics to nonmathematical students. Featuring new coauthor, William Notz and new features, exercises, and applications, the sixth edition of Stastisics: Concepts and Controversies is ready to reveal the power of statistics to a new generation of students.

Booknews

This textbook examines statistical ideas and reasoning and their relevance to public policy and the human sciences from medicine to sociology. It is not intended as a treatment of statistical theory and methods, except as they apply to these issues. Moore (Purdue U.) discusses concepts such as sampling errors, the wording of questions, data ethics, displaying distributions with graphs, scatterplots, correlations, probability models, and the use and abuse of statistical inference. The previous edition's eight chapters have been separated into 25 short ones. Annotation c. Book News, Inc., Portland, OR (booknews.com)

To the Teacher: Statistics as a Liberal Discipline Prelude: Making Sense of Data

I. Producing Data
1. Where Do Data Come From?
2. Samples, Good and Bad
3. What Do Samples Tell Us?
4. Sample Surveys in the Real World
5. Experiments, Good and Bad
6. Experiments in the Real World
7. Data Ethics
8. Measuring
9. Do the Numbers Make Sense?
Review I: Producing Data

II. Organizing Data
10. Graphs Good and Bad
11. Displaying Distributions with Graphs
12. Describing Distributions with Numbers
13. Normal Distributions
14. Describing Relationships: Scatterplots and Correlation
15. Describing Relationships: Regression, Prediction, and Causation
16. The Consumer Price Index and Government Statistics Review II: Organizing Data

III. Chance
17. Thinking about Chance
18. Probability Models
19. Simulation
20. The House Edge: Expected Values Review III: Chance

IV. Inference
21. What is a Confidence Interval?
22. What is a Test of Significance?
23. Use and Abuse of Statistical Inference
24. Two-Way Tables and the Chi-square Test
25. Inference About a Population Means Part IV Review