Lectures on Probability and Statistics for Graduate-Level Economics
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【簡介】
Sound knowledge of rigorous probability and statistics methods is essential to pursue graduate studies in economics. These sorts of tools are largely required to conduct research in modern fields of economics such as economic theory, empirical economics, experimental economics, or data science for economics.
These notes provide an intuitive roadmap to navigate graduate-level courses in mathematical probability and statistics for economists. Each chapter presents questions prevalent on each topic and lays out the state-of-the-art theoretical frameworks used to address such questions. The book offers a diverse array of solved examples to help gain intuitions on abstract concepts, as well as unsolved exercises to stimulate the readers’ training in such concepts. The book presents the theoretical side of probability and statistics in a rather concise way and stresses the importance of motivating examples and observations.
【目錄】
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Probability and Statistics for Economists 2022 (1版)
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PROBABILITY AND STATISTICS FOR ECONOMISTS 2022 (H)
ISBN： 9780691235943
類別： 經濟學Economics
出版社： PRINCETON UNIVERSITY PRESS
作者： HANSEN
年份： 2022
裝訂別： 精裝
頁數： 416頁
Probability theory is the quantitative language used to handle uncertainty and is the foundation of modern statistics. Probability and Statistics for Economists provides graduate and PhD students with an essential introduction to mathematical probability and statistical theory, which are the basis of the methods used in econometrics. This incisive textbook teaches fundamental concepts, emphasizes modern, real-world applications, and gives students an intuitive understanding of the mathematics that every economist needs to know.
> Covers probability and statistics with mathematical rigor while emphasizing intuitive explanations that are accessible to economics students of all backgrounds
> Discusses random variables, parametric and multivariate distributions, sampling, the law of large numbers, central limit theory, maximum likelihood estimation, numerical optimization, hypothesis testing, and more
> Features hundreds of exercises that enable students to learn by doing
> Includes an in-depth appendix summarizing important mathematical results as well as a wealth of real-world examples
> Can serve as a core textbook for a first-semester PhD course in econometrics and as a companion book to Bruce E. Hansen’s Econometrics
> Also an invaluable reference for researchers and practitioners
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Probability and Statistics for Engineers and Scientists (4版)
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書名：Probability and Statistics for Engineers and Scientists 4/e
作者：HAYTER
出版社：Cengage
出版日期：2013/00/00
ISBN：9781111827045
內容簡介
●Composition of the book allows flexibility in the order in which the material is taught. The material has been divided into four sections based on probability (Chapters 1-5), basic statistics (Chapters 6-10), advanced statistical methodologies (Chapters 11-14), and additional topics (Chapters 15-17). The Preface offers suggested paths that instructors may follow based on topic preference, making the book ideal for departments in which different methods of teaching coexist.
●This book can also serve as a handbook of statistical methodologies for undergraduate and graduate engineering students.
●Answers to all odd-numbered problems from the end-of-chapter sections are provided at the back of the book.
●Worked examples (77) and more than 150 data sets represent the many different areas of engineering; for instance, civil, mechanical, electrical, industrial, aerospace, biomedical, textile, chemical, and computing.
●Dozens of graphs, along with graphical tools, help students learn concepts visually.
●To help students grasp concepts, each topic is introduced with references to several real examples from engineering and the sciences. After the topic has been developed technically, a highlighted box reinforces students' learning by summarizing the important points.
●Many examples illustrate proper application of new methodologies, and are developed throughout the chapters as increasingly sophisticated methodologies are considered. This allows students to build on their learning in a manageable way, and understand connections among methodologies.
●Computer Note sections offer tips for using various software packages to perform analysis of data sets, which are referenced in the text and available for download from the book's website.
●The applied presentation emphasizes the understanding of underlying concepts and the application of statistical methodologies.
目錄
1. PROBABILITY THEORY.
2. RANDOM VARIABLES.
3. DISCRETE PROBABILITY DISTRIBUTIONS.
4. CONTINUOUS PROBABILITY DISTRIBUTIONS.
5. THE NORMAL DISTRIBUTION.
6. DESCRIPTIVE STATISTICS.
7. STATISTICAL ESTIMATION AND SAMPLING DISTRIBUTIONS.
8. INFERENCES ON A POPULATION MEAN.
9. COMPARING TWO POPULATION MEANS.
10. DISCRETE DATA ANALYSIS.
11. THE ANALYSIS OF VARIANCE.
12. SIMPLE LINEAR REGRESSION AND CORRELATION.
13. MULTIPLE LINEAR REGRESSION AND NONLINEAR REGRESSION.
14. MULTIFACTOR EXPERIMENTAL DESIGN AND ANALYSIS.
15. NONPARAMETRIC STATISTICAL ANALYSIS.
16. QUALITY CONTROL METHODS.
17. RELIABILITY ANALYSIS AND LIFE TESTING.
Answers to Odd-Numbered Problems.
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