Business Statistics (Third Edition)

Author: Douglas A. Lind, Robert D. Mason, William G. McDaniel, Xu Guoxiang
Publisher:
Publish Date: 2004-10-01
Features: This book, as a classic textbook of statistics, aims to introduce the applications of descriptive statistics and inferential statistics in the field of economics to students in economics, finance, management, marketing, accounting, and other related fields. Since its publication, it has been widely popular and has been reprinted multiple times in countries such as the United States and Canada, being adopted by many higher education institutions. The book covers all aspects of business statistics, totaling fourteen chapters. Chapter 1 introduces the basic concepts of statistics. Chapters 2 and 3 focus on descriptive statistics, where Chapter 2 emphasizes the basic descriptive analysis of data using graphs. Chapter 3, on the other hand, quantitatively describes the data by introducing indicators that reflect the central tendency and dispersion of the data. Chapters 4, 5, and 6 serve as a transition from descriptive statistics to inferential statistics. Starting from Chapter 7, the book enters the introduction of inferential statistics. Among them, Chapter 7 involves one branch of inferential statistics—parameter estimation. Chapters 8 and 9 introduce another branch of inferential statistics—hypothesis testing—under both large sample and small sample conditions. Starting from Chapter 10, the book introduces related topics, including analysis of variance, regression analysis, nonparametric tests, statistical quality control, and more. As a textbook, Business Statistics breaks away from the dry and tedious style of traditional similar textbooks, demonstrating strong readability and applicability. This is primarily reflected in: First, the book places great emphasis on case studies. Each chapter contains numerous case studies, primarily from the field of business and economics. By analyzing these cases and ultimately finding their solutions, readers can greatly improve their ability to apply statistical analysis methods. Second, the book includes many statistical examples. Each chapter generally has 1–2 "statistical examples," mainly introducing the historical applications of certain statistical methods. These contents not only broaden readers' knowledge but also help them understand the background and conditions of applying these statistical methods. Third, the book strongly emphasizes the use of software to achieve statistical analysis functions. The accompanying CD-ROM provides teaching support such as PowerPoint, while also offering students a large number of exercises and solutions during their learning process. Additionally, each chapter ends with exercises, computer operations, and related solutions. In summary, the book is rich in visuals, perfectly blending statistical theory with practical applications. It is not only suitable for undergraduate university students but also for follow-up education and training in related fields, making it an outstanding textbook.