"Different books, different results." This book is different from the lengthy review books. It is designed to help students review all the important math topics when they have only six to eight weeks before the Regents exam. This book uses real Regents questions and shows all necessary steps to solve the problems. Its clear format is like no other.

Is the invention of accounting so useful that, as Charlie Munger once said, "you have to know accounting. It's the language of practical business life. It was a very useful thing to deliver to civilization. I've heard it came to civilization through Venice which of course was once the great commercial power in the Mediterranean"? (WOO 2013) This positive view on accounting can be contrasted with an opposing view by Paul Browne that "the recent [accounting] scandals have brought a new level of attention to the accounting profession as gatekeepers and custodians of social interest." (DUM 2013) Contrary to these opposing views (and other ones as will be discussed in the book), accounting (in relation to addition and subtraction) are neither possible (or impossible) nor desirable (or undesirable) to the extent that the respective ideologues (on different sides) would like us to believe. Of course, this reexamination of different opposing views on accounting does not mean that the study of addition and subtraction is useless, or that those fields (related to accounting)-like bookkeeping, auditing, forensics, info management, finance, philosophy of accounting, accounting ethics, lean accounting, mental accounting, environmental audit, creative accounting, carbon accounting, social accounting, and so on-are unimportant. (WK 2013) In fact, neither of these extreme views is plausible. Rather, this book offers an alternative (better) way to understand the future of accounting in regard to the dialectic relationship between addition and subtraction-while learning from different approaches in the literature but without favoring any one of them (nor integrating them, since they are not necessarily compatible with each other). More specifically, this book offers a new theory (that is, the double-sided theory of accounting) to go beyond the existing approaches in a novel way and is organized in four chapters. This seminal project will fundamentally change the way that we think about accounting in relation to addition and subtraction from the combined perspectives of the mind, nature, society, and culture, with enormous implications for the human future and what I originally called its "post-human" fate.

Nowadays, students are struggling to learn math and pass exams. They are overwhelmed with information from lengthy textbooks, review books, and many math websites. With limited time, students cannot benefit from all these resources. Our students need only one concise book to help them review and prepare for the Geometry Regents exam. This is the book "No more. No less. Just right." This book is structured in three parts: 1. A Geometry review that will help students remember all the key topics and build their problem solving skills through the use of examples. 2. A practice section with real Regents questions. 3. Answers and explanations. The topics for the practice questions correspond to the sections in the Geometry review. Students can easily refer back to the matching review sections, while they are doing the practice. This review book is geared towards helping students succeed with high scores on the Regents exams.

Strategy and Statistics in Clinical Trials deals with the research processes and the role of statistics in these processes. The book offers real-life case studies and provides a practical, how to guide to biomedical R&D. It describes the statistical building blocks and concepts of clinical trials and promotes effective cooperation between statisticians and important other parties. The discussion is organized around 15 chapters. After providing an overview of clinical development and statistics, the book explores questions when planning clinical trials, along with the attributes of medical products. It then explains how to set research objectives and goes on to consider statistical thinking, estimation, testing procedures, and statistical significance, explanation and prediction. The rest of the book focuses on exploratory and confirmatory clinical trials; hypothesis testing and multiplicity; elements of clinical trial design; choosing trial endpoints; and determination of sample size. This book is for all individuals engaged in clinical research who are interested in a better understanding of statistics, including professional clinical researchers, professors, physicians, and researchers in laboratory. It will also be of interest to corporate and government laboratories, clinical research nurses, members of the allied health professions, and post-doctoral and graduate students.

The book will benefit a reader with a background in physical sciences and applied mathematics interested in the mathematical models of genetic evolution. In the first chapter, we analyze several thought experiments based on a basic model of stochastic evolution of a single genomic site in the presence of the factors of random mutation, directional natural selection, and random genetic drift. In the second chapter, we present a more advanced theory for a large number of linked loci. In the third chapter, we include the effect of genetic recombination into account and find out the advantage of sexual reproduction for adaptation. These models are useful for the evolution of a broad range of asexual and sexual populations, including virus evolution in a host and a host population.

This book shows that research contributions from different fields-finance, economics, computer sciences, and physics-can provide useful insights into key issues in financial and cryptocurrency markets. Presenting the latest empirical and theoretical advances, it helps readers gain a better understanding of financial markets and cryptocurrencies. Bitcoin was the first cryptocurrency to use a peer-to-peer network to prevent double-spending and to control its issue without the need for a central authority, and it has attracted wide public attention since its introduction. In recent years, the academic community has also started gaining interest in cyptocurrencies, and research in the field has grown rapidly. This book presents is a collection of the latest work on cryptocurrency markets and the properties of those markets. This book will appeal to graduate students and researchers from disciplines such as finance, economics, financial engineering, computer science, physics and applied mathematics working in the field of financial markets, including cryptocurrency markets.

This volume is an outgrowth of the Conference on Research on the Enacted Mathematics Curriculum, funded by the National Science Foundation and held in Tampa, Florida in November 2010. The volume has the potential to be useful to a range of researchers, from established veterans in curriculum research to new researchers in this area of mathematics education. The chapters can be used to generate conversation about researching the enacted mathematics curriculum, including similarities and differences in the variables that can and should be studied across various curricula. As such, it might be used by a curriculum project team as it outlines a research agenda for curriculum or program evaluation. It might also be used as a text in a university graduate course on curriculum research and design. The chapters in this volume are a natural complement to those in Approaches to Studying the Enacted Mathematics Curriculum (Heck, Chval, Weiss, & Ziebarth, 2012), also published by Information Age Publishing. While the present volume focuses on a range of issues related to researching the enacted mathematics curriculum, including theoretical and conceptual issues, the volume by Heck et al. provides insights into different instrumentations used by groups of researchers to study curriculum enactment.

This book is devoted to the study of stochastic measures (SMs). An SM is a sigma-additive in probability random function, defined on a sigma-algebra of sets. SMs can be generated by the increments of random processes from many important classes such as square-integrable martingales and fractional Brownian motion, as well as alpha-stable processes. SMs include many well-known stochastic integrators as partial cases.General Stochastic Measures provides a comprehensive theoretical overview of SMs, including the basic properties of the integrals of real functions with respect to SMs. A number of results concerning the Besov regularity of SMs are presented, along with equations driven by SMs, types of solution approximation and the averaging principle. Integrals in the Hilbert space and symmetric integrals of random functions are also addressed.The results from this book are applicable to a wide range of stochastic processes, making it a useful reference text for researchers and postgraduate or postdoctoral students who specialize in stochastic analysis.

Rank-Based Methods for Shrinkage and Selection A practical and hands-on guide to the theory and methodology of statistical estimation based on rank Robust statistics is an important field in contemporary mathematics and applied statistical methods. Rank-Based Methods for Shrinkage and Selection: With Application to Machine Learning describes techniques to produce higher quality data analysis in shrinkage and subset selection to obtain parsimonious models with outlier-free prediction. This book is intended for statisticians, economists, biostatisticians, data scientists and graduate students. Rank-Based Methods for Shrinkage and Selection elaborates on rank-based theory and application in machine learning to robustify the least squares methodology. It also includes: Development of rank theory and application of shrinkage and selection Methodology for robust data science using penalized rank estimators Theory and methods of penalized rank dispersion for ridge, LASSO and Enet Topics include Liu regression, high-dimension, and AR(p) Novel rank-based logistic regression and neural networks Problem sets include R code to demonstrate its use in machine learning

This accessible reference includes selected contributions from Bayesian Thinking - Modeling and Computation, Volume 25 in the Handbook of Statistics Series, with a focus on key methodologies and applications for Bayesian models and computation. It describes parametric and nonparametric Bayesian methods for modeling, and how to use modern computational methods to summarize inferences using simulation. The book covers a wide range of topics including objective and subjective Bayesian inferences, with a variety of applications in modeling categorical, survival, spatial, spatiotemporal, Epidemiological, small area and micro array data.

Aids critical thinking on causal effects
Provides simulation based computing techniques
Covers Bioinformatics and Biostatistics

This volume is number ten in the 11-volume Handbook of the History of Logic. While there are many examples were a science split from philosophy and became autonomous (such as physics with Newton and biology with Darwin), and while there are, perhaps, topics that are of exclusively philosophical interest, inductive logic - as this handbook attests - is a research field where philosophers and scientists fruitfully and constructively interact. This handbook covers the rich history of scientific turning points in Inductive Logic, including probability theory and decision theory. Written by leading researchers in the field, both this volume and the Handbook as a whole are definitive reference tools for senior undergraduates, graduate students and researchers in the history of logic, the history of philosophy, and any discipline, such as mathematics, computer science, cognitive psychology, and artificial intelligence, for whom the historical background of his or her work is a salient consideration.

Chapter on the Port Royal contributions to probability theory and decision theory

Serves as a singular contribution to the intellectual history of the 20th century Contains the latest scholarly discoveries and interpretative insights"

This book describes methods for statistical brain imaging data analysis from both the perspective of methodology and from the standpoint of application for software implementation in neuroscience research. These include those both commonly used (traditional established) and state of the art methods. The former is easier to do due to the availability of appropriate software. To understand the methods it is necessary to have some mathematical knowledge which is explained in the book with the help of figures and descriptions of the theory behind the software. In addition, the book includes numerical examples to guide readers on the working of existing popular software. The use of mathematics is reduced and simplified for non-experts using established methods, which also helps in avoiding mistakes in application and interpretation. Finally, the book enables the reader to understand and conceptualize the overall flow of brain imaging data analysis, particularly for statisticians and data-scientists unfamiliar with this area. The state of the art method described in the book has a multivariate approach developed by the authors' team. Since brain imaging data, generally, has a highly correlated and complex structure with large amounts of data, categorized into big data, the multivariate approach can be used as dimension reduction by following the application of statistical methods. The R package for most of the methods described is provided in the book. Understanding the background theory is helpful in implementing the software for original and creative applications and for an unbiased interpretation of the output. The book also explains new methods in a conceptual manner. These methodologies and packages are commonly applied in life science data analysis. Advanced methods to obtain novel insights are introduced, thereby encouraging the development of new methods and applications for research into medicine as a neuroscience.