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Description
Applied Statistics presents a thorough treatment of the methods of regression and analysis of variance. The book focuses on conceptual understandings of statistical methods in regression and analysis of variance as well as the use of statistical software to obtain correct results. Real data examples from many fields of study are used to motivate the presentation and illustrate the concepts and methods. Almost all of the examples in the book are accompanied with their corresponding SAS programs. The R programs are available on the following website: http://people.cst.cmich.edu/famoy1kf/appliedstat. This textbook is user-friendly and simplifies the presentation of complicated material. Applied Statistics requires an understanding of introductory statistics courses and is suitable for both junior and senior undergraduate students.
Table of Contents
2: Simple Linear Regression
3: Inferences on Parameter Estimates
4: Mutiple Linear Regression
5: Regression Diagnostics and Remedial Methods
6: Multiple and Partial Correlations
7: Model Selection Strategies
8: Use of Dummy Variables in Regression Analysis
9: Polynomial Regression
10: Logistic Regression
11: Count Data Regression Models
12: Regression with Censored of Truncated Data
13: Nonlinear Regression
14: One-Way Analysis of Variance
15: Two-Factor Analysis of Variance
16: Analysis of Covariance
17: Randomized Complete Block Design
18: Non Orthogonal Classification
Product details
Published | Aug 09 2013 |
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Format | Paperback |
Edition | 1st |
Extent | 544 |
ISBN | 9780761861713 |
Imprint | University Press of America |
Illustrations | 259 Tables |
Dimensions | 11 x 9 inches |
Publisher | Bloomsbury Publishing |