Statistical Methods, Fourth Edition, is designed to introduce students to a wide-range of popular and practical statistical techniques. Requiring a minimum of advanced mathematics, it is suitable for undergraduates in statistics, or graduate students in the physical, life, and social sciences. By providing an overview of statistical reasoning, this text equips readers with the insight needed to summarize data, recognize good experimental designs, implement appropriate analyses, and arrive at sound interpretations of statistical results. - Includes extensive case studies and exercises drawn from a variety of disciplines - Provides practice problems for each chapter with complete solutions - Offers new and updated data sets available online - Includes recommended data analysis projects with accompanying data sets
Autorentext
Donna Mohr is a Professor Emeritus of Statistics at the University of North Florida, where she was a colleague of William Wilson. She is an author on 20 scholarly articles on theoretical statistics and its applications. During her decades of teaching statistics, she used both the first and second editions of Freund and Wilson's Statistical Methods, before joining as a co-author in the third edition.
Klappentext
Statistical Methods, Fourth Edition, is designed to introduce students to a wide-range of popular and practical statistical techniques. Requiring a minimum of advanced mathematics, it is suitable for undergraduates in statistics, or graduate students in the physical, life, and social sciences. By providing an overview of statistical reasoning, this text equips readers with the insight needed to summarize data, recognize good experimental designs, implement appropriate analyses, and arrive at sound interpretations of statistical results.
- Includes extensive case studies and exercises drawn from a variety of disciplines
- Provides practice problems for each chapter with complete solutions
- Offers new and updated data sets available online
- Includes recommended data analysis projects with accompanying data sets
Inhalt
1. Data and statistics
2. Probability and sampling distributions
3. Principles of inference
4. Inferences on a single population
5. Inferences for two populations
6. Inferences for two or more means
7. Linear regression
8. Multiple regression
9. Linear models
10. Factorial experiments
11. Design of experiments
12. Categorical data
13. Generalized linear models
14. Nonparametric methods