Statistical Methods, 3e provides students with a working introduction to statistical methods offering a wide range of applications that emphasize the quantitative skills useful across many academic disciplines. This text takes a classic approach emphasizing concepts and techniques for working out problems and intepreting results. The book includes research projects, real-world case studies, numerous examples and data exercises organized by level of difficulty. This text requires that a student be familiar with algebra.
New to this edition:
- NEW expansion of exercises applying different techniques and methods
- NEW examples and datasets using current real-world data
- New text organization to create a more natural connection between regression and the Analysis of the Variance
- NEW material on generalized linear models
- NEW expansion of nonparametric techniques
- NEW student research projects
- NEW case studies for gathering, summarizing, and analyzing data
- NEW companion website with downloadable data sets and additional resources including live links to statistical software such as SAS and SPSS
- Student Solutions Manual - to come
- Instructor Manual - to come
- Sample chapter - http://www.elsevierdirect.com/product.jsp?isbn=9780123749703
- Integrates the classical conceptual approach with modern day computerized data manipulation and computer applications
- Accessibile to students who may not have a background in probability or calculus
- Offers reader-friendly exposition, without sacrificing statistical rigor
- Includes many new data sets in various applied fields such as Psychology, Education, Biostatistics, Agriculture, Economics
Advanced undergraduates majoring or minoring in statistics, math or graduate students in an applied field requiring statistical methods: psychology, public administration, economics, sociology, education, public health, engineering, agriculture.
- 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
- No. of pages:
- © Academic Press 2010
- 6th July 2010
- Academic Press
- eBook ISBN:
- Hardcover ISBN:
Texas A&M University, U.S.A.
University of North Florida, Jacksonville, Florida, U.S.A.