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Data Analysis Using SAS

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This comprehensive core text focuses on key concepts and techniques in quantitative data analysis using the latest SAS commands and programming language. It balances coverage among statistical analysis, SAS programming, and data/file management more effectively than any other text available. Students engage in a hands-on, exercise-heavy approach to learn basic to intermediate SAS commands while applying statistics and reasoning to real-world problems. The book is structured to align with instructors' teaching preferences, divided into two main sections. The first half covers data and file management techniques, including concatenating and merging files, as well as conditional or repetitive processing of variables and observations. The second half delves deeply into common statistical techniques and concepts, such as descriptive statistics, correlation, analysis of variance, and regression, relevant for analyzing data in the social, behavioral, and health sciences using SAS commands. Additionally, it includes a wealth of computer programs, their outputs, guidance on checking assumptions, and all data sets utilized in the text. This resource serves as a complete guide for courses in Data Analysis I and II, Statistics I and II, Quantitative Reasoning, and SAS Programming across social and behavioral sciences and health, particularly those with a lab component.

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Data Analysis Using SAS, Chao-Ying Joanne Peng

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Released
2008
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Title
Data Analysis Using SAS
Language
English
Released
2008
Format
Paperback
Pages
640
ISBN10
1412956749
ISBN13
9781412956741
Series
Description
This comprehensive core text focuses on key concepts and techniques in quantitative data analysis using the latest SAS commands and programming language. It balances coverage among statistical analysis, SAS programming, and data/file management more effectively than any other text available. Students engage in a hands-on, exercise-heavy approach to learn basic to intermediate SAS commands while applying statistics and reasoning to real-world problems. The book is structured to align with instructors' teaching preferences, divided into two main sections. The first half covers data and file management techniques, including concatenating and merging files, as well as conditional or repetitive processing of variables and observations. The second half delves deeply into common statistical techniques and concepts, such as descriptive statistics, correlation, analysis of variance, and regression, relevant for analyzing data in the social, behavioral, and health sciences using SAS commands. Additionally, it includes a wealth of computer programs, their outputs, guidance on checking assumptions, and all data sets utilized in the text. This resource serves as a complete guide for courses in Data Analysis I and II, Statistics I and II, Quantitative Reasoning, and SAS Programming across social and behavioral sciences and health, particularly those with a lab component.