Discovering statistics using SAS : and sex and drugs and rock 'n' roll

著者

書誌事項

Discovering statistics using SAS : and sex and drugs and rock 'n' roll

Andy Field and Jeremy Miles

SAGE, 2010

  • : hard
  • : pbk

大学図書館所蔵 件 / 全4件

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注記

Includes bibliographical references and index

内容説明・目次

内容説明

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 (R). 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 (R) 9.2. If you're using SAS (R), 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 (R). A 'cast of characters' supports the learning process throughout the book, from providing tips on how to enter data in SAS (R) 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.

目次

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

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