"The Foundations of AP Statistics" is not your typical test preparation book. It's better.True, inside you'll find many of the standard features of such prep books: thorough reviews of the topics recommended by the AP Development Committee, dozens and dozens of questions designed to reinforce the concepts (with detailed explanations accompanying the answers), AP Exam tips and shortcuts, and a full-length practice exam.But this book addresses a critical, and often ignored, need by offering a mathematically rigorous and intellectually expansive approach to all of the AP Statistics topics. It is not enough to merely direct you to make use of particular statistical tools without offering detailed justification of when and why you need to use them. It is not enough to offer you a "Just the facts, ma'am"-style of presentation and yet still expect you to retain mass amounts of information for the AP Exam. In short: it is not enough to explore the forest without closely examining the trees. Yes, that means proofs are oftentimes necessary, some of which will require a bit of calculus. It also means real-world examples, taken from a variety of disciplines, are of paramount importance.The theory behind "The Foundations of AP Statistics" is simple: by being exposed to and working through complex material a significant cut above that which is required for an AP Statistics course, the AP Exam will be relatively easy to ace. Think of this book's approach as "Honors" AP Statistics: gaining exposure to the practice of statistics, coupled with a deep mathematical understanding of the nature of the statistical tools themselves, will better prepare you for both the routine sorts of AP questions as well as the more esoteric, non-routine ones. It's advanced preparation for the Advanced Placement Statistics Exam.So, if you are an AP Statistics (or college statistics) student looking for a more challenging, more mathematically rigorous, more comprehensive, more grounded, and more holistically integrated approach to the material than is typically offered by other popular preparation books, textbooks, or online resources--or even by your teacher (or professor)--then this book is for you. If you are a high school (or college) student especially interested in math and statistics, but never got around to taking a statistics course, then this book is for you. If you're a teacher (or professor) looking for ways to insert more mathematically meaningful and contextually relevant content into your AP Statistics (or introductory statistics) class, rather than simply glossing over the mathematics and the major historical players, then this book is for you. Or if you are simply among the intellectually curious looking for a cogent gateway toward an understanding of probability and statistics, ready to put on firmer intellectual footing your ability to think statistically--which novelist H. G. Wells once identified "as necessary for efficient citizenship as the ability to read and write"--then this book is most definitely for you.Take a chance on statistical enlightenment--and earn yourself a 5 in the process. * AP and Advanced Placement Program are registered trademarks of the College Board, which was not involved in the production of, and does not endorse, this product.
Quantum statistics by Aleksandr I︠A︡kovlevich Khinchin
This important collection of essays is a synthesis of foundational studies in Bayesian decision theory and statistics. An overarching topic of the collection is understanding how the norms for Bayesian decision making should apply in settings with more than one rational decision maker and then tracing out some of the consequences of this turn for Bayesian statistics. The volume will be particularly valuable to philosophers concerned with decision theory, probability, and statistics, statisticians, mathematicians, and economists.
In May of 1973 we organized an international research colloquium on foundations of probability, statistics, and statistical theories of science at the University of Western Ontario. During the past four decades there have been striking formal advances in our understanding of logic, semantics and algebraic structure in probabilistic and statistical theories. These advances, which include the development of the relations between semantics and metamathematics, between logics and algebras and the algebraic-geometrical foundations of statistical theories (especially in the sciences), have led to striking new insights into the formal and conceptual structure of probability and statistical theory and their scientific applications in the form of scientific theory. The foundations of statistics are in a state of profound conflict. Fisher's objections to some aspects of Neyman-Pearson statistics have long been well known. More recently the emergence of Bayesian statistics as a radical alternative to standard views has made the conflict especially acute. In recent years the response of many practising statisticians to the conflict has been an eclectic approach to statistical inference. Many good statisticians have developed a kind of wisdom which enables them to know which problems are most appropriately handled by each of the methods available. The search for principles which would explain why each of the methods works where it does and fails where it does offers a fruitful approach to the controversy over foundations.
Basic Statistics with R: Reaching Decisions with Data provides an understanding of the processes at work in using data for results. Sections cover data collection and discuss exploratory analyses, including visual graphs, numerical summaries, and relationships between variables - basic probability, and statistical inference - including hypothesis testing and confidence intervals. All topics are taught using real-data drawn from various fields, including economics, biology, political science and sports. Using this wide variety of motivating examples allows students to directly connect and make statistics essential to their field of interest, rather than seeing it as a separate and ancillary knowledge area. In addition to introducing students to statistical topics using real data, the book provides a gentle introduction to coding, having the students use the statistical language and software R. Students learn to load data, calculate summary statistics, create graphs and do statistical inference using R with either Windows or Macintosh machines. Features real-data to give students an engaging practice to connect with their areas of interest Evolves from basic problems that can be worked by hand to the elementary use of opensource R software Offers a direct, clear approach highlighted by useful visuals and examples
Quantum statistics by Aleksandr I︠A︡kovlevich Khinchin
Features coverage of the service systems lifecycle, including service marketing, engineering, delivery, quality control, management, and sustainment Featuring an innovative and holistic approach, Service Science: The Foundations of Service Engineering and Management provides a new perspective of service research and practice. The book presents a practical approach to the service systems lifecycle framework, which aids in understanding and capturing market trends; analyzing the design and engineering of service products and delivery networks; executing service operations; and controlling and managing the service lifecycles for competitive advantage. Utilizing a combined theoretical and practical approach to discuss service science, Service Science: The Foundations of Service Engineering and Management also features: Case studies to illustrate how the presented theories and design principles are applied in practice to the definitions of fundamental service laws, including service interaction and socio-technical natures Computational thinking and system modeling such as abstraction, digitalization, holistic perspectives, and analytics Plentiful examples of service organizations such as automobile after-sale services, global project management networks, and express delivery services An interdisciplinary emphasis that includes integrated approaches from the fields of mathematics, engineering, industrial engineering, business, operations research, and management science A detailed analysis of the key concepts and body of knowledge for readers to master the foundations of service management Service Science: The Foundations of Service Engineering and Management is an ideal reference for practitioners in the contemporary service engineering and management field as well as researchers in applied mathematics, statistics, business/management science, operations research, industrial engineering, and economics. The book is also appropriate as a text for upper-undergraduate and graduate-level courses in industrial engineering, operations research, and management science as well as MBA students studying service management.
An update to the original 1992 publication, this two-volume set unites current research to provide new conceptualizations of research problems, and to suggest possible research programs to move the field forward. In studying the existing research, the authors found that the community has maintained its focus on problems of learning, teaching, teacher education, assessment, technology, and social and cultural aspects of mathematics education, while some new areas of interest have emerged or been expanded. This set allows educators to step back and look at each of these areas to see where mathematics education research has been and where it should be going to enable the field to answer the questions about education that practitioners, policy makers, and politicians are asking.