基本説明
Takes the entry-level student from first principles right the way through to advanced-level statistical concepts all the while grounding knowledge through the use of SAS.
Full Description
Hot on the heels of the 3rd edition of Andy Field's award-winning Discovering Statistics Using SPSS comes this brand new version for students using SAS®. Andy has teamed up with a co-author, Jeremy Miles, to adapt the book with all the most up-to-date commands and programming language from SAS® 9.2. If you're using SAS®, this is the only book on statistics that you will need! The book provides a comprehensive collection of statistical methods, tests and procedures, covering everything you're likely to need to know for your course, all presented in Andy's accessible and humourous writing style. Suitable for those new to statistics as well as students on intermediate and more advanced courses, the book walks students through from basic to advanced level concepts, all the while reinforcing knowledge through the use of SAS®.
A 'cast of characters' supports the learning process throughout the book, from providing tips on how to enter data in SAS® properly to testing knowledge covered in chapters interactively, and 'real world' and invented examples illustrate the concepts and make the techniques come alive.
The book's companion website (see link above) provides students with a wide range of invented and real published research datasets. Lecturers can find multiple choice questions and PowerPoint slides for each chapter to support their teaching.
Contents
Why Is My Evil Lecturer Forcing Me to Learn Statistics?
Everything You Ever Wanted to Know about Statistics (Well, Sort of)
The SAS Environment
Exploring Data with Graphs
Exploring Assumptions
Correlation
Regression
Logistic Regression
Comparing Two Means
Comparing Several Means: ANOVA (GLM 1)
Analysis of Covariance, ANCOVA (GLM 2)
Factorial ANOVA (GLM 3)
Repeated-Measures Designs (GLM 4)
Mixed Design ANOVA (GLM 5)
Non-Parametric Tests
Multivariate Analysis of Variance (MANOVA)
Exploratory Factor Analysis
Categorical Data
Multilevel Linear Models
