"Applied Statistics and the SAS Programming Language" by Ronald P. Cody is an extensive guide that brings together statistical concepts and practical applications using the SAS programming language. This book is suitable for both beginners and experienced statisticians aiming to enhance their statistical skills and learn how to implement them using SAS.
The book starts with an introduction to SAS programming, making it accessible to newcomers to the software. It provides step-by-step instructions on conducting basic statistical analyses using SAS, including descriptive statistics, hypothesis testing, and regression analysis. The author also offers clear explanations on interpreting the results and supports the concepts with real-world examples.
One of the standout features of this book is its emphasis on practical applications. Each statistical concept is presented in the context of its relevance to real-world problems and datasets. Cody includes numerous examples and exercises throughout the book, allowing readers to practice and reinforce their understanding of the material. This hands-on approach helps readers to apply statistical techniques effectively.
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In addition to statistical analysis, this book also focuses on data management. Cody goes beyond the analysis itself and explains how to import, clean, and manipulate data using SAS. This is particularly valuable for readers dealing with large or messy datasets that require preprocessing. The author provides useful tips and tricks for data preparation, which can save time and enhance efficiency.
Overall, "Applied Statistics and the SAS Programming Language" is a valuable resource for individuals looking to learn or improve their statistical analysis skills using SAS. It offers a solid foundation in statistical concepts, presents practical examples, and demonstrates how to implement these concepts using the SAS programming language. Whether you are a beginner or an experienced SAS user, this book will help you develop the necessary skills to perform effective statistical analysis.
What are readers saying?
The book "Applied Statistics and the SAS Programming Language" by Ronald P. Cody has received mixed reviews from readers. While some readers have found it to be a comprehensive guide to applied statistics using SAS, others have expressed disappointment with its outdated content and lack of practical examples.
Several reviewers have praised the book for its clear and concise explanations of statistical concepts. They appreciate how the author integrates these concepts with the SAS programming language, making it easier for readers to apply statistical techniques in real-world scenarios. The book is also commended for its thorough coverage of topics such as data visualization, linear regression, and hypothesis testing.
However, some readers have criticized the book for its dated content and examples. They feel that the text has not been updated to reflect recent advancements in statistical techniques and SAS programming. Additionally, some reviewers mention that the book lacks practical examples and case studies, which they believe would have enhanced their understanding and application of the material.
Another aspect of the book that has received mixed feedback is its level of difficulty. Some readers have found the explanations to be too technical and challenging, making it difficult for beginners to grasp the concepts. On the other hand, experienced statisticians appreciate the level of detail provided in the book and find it valuable for advanced study.
Despite these criticisms, the majority of readers believe that "Applied Statistics and the SAS Programming Language" is a useful resource for learning applied statistics with SAS. They appreciate the book's comprehensive coverage of statistical concepts and its integration with SAS programming. However, there is a general consensus that the book would benefit from updates to reflect current practices and include more practical examples to enhance the learning experience.
AppliedStatistics SASProgrammingLanguage DataAnalysis