The book is a review of some basics notions in optics. The first chapter starts with a review of Newton's laws and planetary motion and some related equations. The second chapter deals with the planet earth's atmosphere; the third is an introduction to remote sensing. Chapter 4 and 5 introduce a background on Maxwell's laws in electromagnetism and light polarization. Some other topics of interest have been also developed. Among these topics are the light interaction with spherical surfaces and related equations, light Interference, linear polarization by anisotropy, Fourier transform spectroscopy, and an introduction to Lidar.

Boltzmann and Vlasov equations played a great role in the past and still play an important role in modern natural sciences, technique and even philosophy of science. Classical Boltzmann equation derived in 1872 became a cornerstone for the molecular-kinetic theory, the second law of thermodynamics (increasing entropy) and derivation of the basic hydrodynamic equations. After modifications, the fields and numbers of its applications have increased to include diluted gas, radiation, neutral particles transportation, atmosphere optics and nuclear reactor modelling. Vlasov equation was obtained in 1938 and serves as a basis of plasma physics and describes large-scale processes and galaxies in astronomy, star wind theory. This book provides a comprehensive review of both equations and presents both classical and modern applications. In addition, it discusses several open problems of great importance.

Written for students with basic experience in college algebra and applied calculus, Fundamentals of Statistical Thinking: Tools and Applications familiarizes readers with fundamental concepts in statistical thinking in order to prepare them for specialized management courses such as econometrics and quantitative analysis. The book is organized into four sections, each of which focuses on a common tool used in application. Chapters 1 through 4 discuss data analysis and summaries, with an emphasis on descriptive statistics and visualization. In Chapters 5 through 8 students learn about probability models and sampling distributions. Chapters 9 and 10 deal with statistical inferences, while Chapters 11 and 12 provide further applications for categorical data and simple linear regression models. Graphical illustrations support the written text and each chapter concludes with a visual summary. Rooted in over ten years of classroom experience at both the undergraduate and graduate levels, Fundamentals of Statistical Thinking helps readers understand the importance of the main technical tools of statistical decision making, and explains when they can most appropriately be used for applied studies.

This is a guide, in theory and in practice, to how current technological changes have impacted our interaction with texts and with each other. Henry Sussman rereads pivotal moments in literary, philosophical and cultural modernity as anticipating the cybernetic discourse that has increasingly defined theory since the computer revolution. Cognitive science, psychoanalysis and systems theory are paralleled to current trends in literary and philosophical theory. Chapters alternate between theory and readings of literary texts, resulting in a broad but rigorously grounded framework for the relation between literature and computer science. This book is a refreshing perspective on the analog-orientated tradition of theory in the humanities - and offers the first literary-textual genealogy of the digital.

With a long history of innovation in the market, Larson/Edwards' Calculus, International Metric Edition has been widely praised by a generation of students and professors for solid and effective pedagogy that addresses the needs of a broad range of teaching and learning styles and environments. This edition clearly presents and effectively demonstrates the concepts and rules of calculus with a student-focused approach. It offers a wealth of learning support and digital resources - all thoroughly updated and refined using proven learning design principles that remove typical barriers to learning to create a carefully planned, inclusive experience for all students.

This bookdescribes computational financetools. It covers fundamental numerical analysis and computational techniques, such asoption pricing, and givesspecial attention tosimulation and optimization. Many chapters are organized as case studies aroundportfolio insurance and risk estimation problems. In particular, several chapters explain optimization heuristics and how to use them for portfolio selection and in calibration of estimation and option pricing models. Such practical examples allow readers to learn the steps for solving specific problems and apply these steps to others. At the same time, the applications are relevant enough to make the book a useful reference. Matlab and R sample code is provided in the text and can be downloaded from the book's website.
Shows ways to build and implement tools that help test ideasFocuses on the application of heuristics; standard methods receive limited attentionPresents as separate chapters problems from portfolio optimization, estimation of econometric models, and calibration of option pricing models"

"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.

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.

Exploring Monte Carlo Methods is a basic text that describes the numerical methods that have come to be known as "Monte Carlo." The book treats the subject generically through the first eight chapters and, thus, should be of use to anyone who wants to learn to use Monte Carlo. The next two chapters focus on applications in nuclear engineering, which are illustrative of uses in other fields. Five appendices are included, which provide useful information on probability distributions, general-purpose Monte Carlo codes for radiation transport, and other matters. The famous "Buffon s needle problem" provides a unifying theme as it is repeatedly used to illustrate many features of Monte Carlo methods.

This book provides the basic detail necessary to learn how to apply Monte Carlo methods and thus should be useful as a text book for undergraduate or graduate courses in numerical methods. It is written so that interested readers with only an understanding of calculus and differential equations can learn Monte Carlo on their own. Coverage of topics such as variance reduction, pseudo-random number generation, Markov chain Monte Carlo, inverse Monte Carlo, and linear operator equations will make the book useful even to experienced Monte Carlo practitioners.
Provides a concise treatment of generic Monte Carlo methods
Proofs for each chapter
Appendixes include Certain mathematical functions; Bose Einstein functions, Fermi Dirac functions, Watson functions"

The innovative use of sliceforms to explore the properties of surfaces is produced in a systematic way, providing the tools to build surfaces from paper to explore their mathematics. The extensive commentary explains the mathematics behind particular surfaces: an exercise in practical geometry that will stimulate ideas for the student and the enthusiast, as well as having practical applications in engineering and architecture.

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.