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Cengage Learning Statistical Inference: Essential Guide for Data Analysis and Probability Theory
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Product Description
This book builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. Intended for first-year graduate students, this book is an excellent resource for students majoring in statistics who possess a solid mathematics background. It can also be utilized in a way that emphasizes the more practical uses of statistical theory, focusing on understanding basic statistical concepts and deriving reasonable statistical procedures for a variety of situations rather than merely formal optimality investigations.
Key Features
- Comprehensive Coverage: Offers new coverage of random number generation, simulation methods, bootstrapping, EM algorithm, p-values, and robustness.
- Updated Content: Includes new sections on Logistic Regression and Robust Regression that enhance the learning experience.
- Clear Structure: Restructures material for clarity purposes, making complex concepts more accessible to students.
- Expanded Exercises: Contains updated and expanded exercises that encourage practical application of theoretical concepts.
- Brand Authority: Published by Cengage Learning India Pvt., known for its commitment to high-quality educational resources.
This book is a vital addition to the educational resources of anyone pursuing a career in statistics. It not only covers theoretical foundations but also applies those principles to real-world scenarios. The focus on statistical inference is particularly important for students who will be engaging in research or applied statistics in their future careers. By integrating practical examples with theoretical knowledge, this book prepares students for challenges they may face in professional environments.
In addition to the core content, the book?s features, such as expanded exercises and clear restructuring, provide a robust framework for learning. Each chapter is designed to build upon the last, ensuring that students develop a deep and comprehensive understanding of statistical inference.
Whether you are a graduate student or an educator seeking a valuable teaching tool, this book serves as a comprehensive guide to understanding statistical theory and its applications. The combination of theory and practice makes it an essential resource for anyone interested in mastering the field of statistics.
Enhance your statistical knowledge and skills today with this authoritative text from Cengage Learning.
⚠️ WARNING (California Proposition 65):
This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.
For more information, please visit www.P65Warnings.ca.gov.
- Q: What topics are covered in 'Statistical Inference'? A: 'Statistical Inference' covers a range of topics including probability theory, the theory of statistical inference, random number generation, simulation methods, bootstrapping, the EM algorithm, p-values, robustness, logistic regression, and robust regression.
- Q: Who is the intended audience for this book? A: This book is intended for first-year graduate students, particularly those majoring in statistics with a solid background in mathematics.
- Q: What is the format of the book? A: 'Statistical Inference' is available in paperback format and consists of 700 pages.
- Q: When was 'Statistical Inference' published? A: 'Statistical Inference' was published on December 1, 2007.
- Q: What are the key features of 'Statistical Inference'? A: Key features of the book include new coverage of important statistical methods, updated and expanded exercises, and material restructured for clarity.
- Q: Is 'Statistical Inference' suitable for practical applications? A: Yes, the book emphasizes understanding basic statistical concepts and deriving reasonable statistical procedures for various real-world situations.
- Q: Who is the author of 'Statistical Inference'? A: The author of 'Statistical Inference' is George Casella.
- Q: Is this book suitable for self-study? A: Yes, 'Statistical Inference' can be used for self-study, especially for students who are comfortable with advanced mathematics.
- Q: Are there exercises included in 'Statistical Inference'? A: Yes, the book contains updated and expanded exercises to reinforce learning and understanding of statistical concepts.
- Q: What is the condition of the book? A: 'Statistical Inference' is available in new condition.