|
Product Description
Praise for the Third Edition
"...this is an excellent book which could easily be used as a course text..."
―International Statistical Institute
The Fourth Edition of Applied Linear Regression provides a thorough update of the basic theory and methodology of linear regression modeling. Demonstrating the practical applications of linear regression analysis techniques, the Fourth Edition uses interesting, real-world exercises and examples.
Stressing central concepts such as model building, understanding parameters, assessing fit and reliability, and drawing conclusions, the new edition illustrates how to develop estimation, confidence, and testing procedures primarily through the use of least squares regression. While maintaining the accessible appeal of each previous edition,Applied Linear Regression, Fourth Edition features:
- Graphical methods stressed in the initial exploratory phase, analysis phase, and summarization phase of an analysis
- In-depth coverage of parameter estimates in both simple and complex models, transformations, and regression diagnostics
- Newly added material on topics including testing, ANOVA, and variance assumptions
- Updated methodology, such as bootstrapping, cross-validation binomial and Poisson regression, and modern model selection methods
Applied Linear Regression, Fourth Edition is an excellent textbook for upper-undergraduate and graduate-level students, as well as an appropriate reference guide for practitioners and applied statisticians in engineering, business administration, economics, and the social sciences.
Customers Who Bought This Item Also Bought
- Statistical Inference
- Linear Models with R (Chapman & Hall/CRC Texts in Statistical Science)
- Applied Logistic Regression
- The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
- Mathematical Statistics with Applications
- Applied Longitudinal Analysis
- An R Companion to Applied Regression (NULL)
- An Introduction to Statistical Learning: with Applications in R (Springer Texts in Statistics)
- Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models, Second Edition (Chapman & Hall/CRC Texts in Statistical Science)
- Statistical Inference
*If this is not the "Applied Linear Regression" product you were looking for, you can check the other results by clicking this link. Details were last updated on Dec 23, 2024 01:23 +08.