Functions Data And Models

Focuses primarily on mathematical concepts and mathematical thinking, thereby achieving a balance among geometric, numerical, symbolic, and statistical approaches, rather than focusing on algebraic manipulation. Gordon incorporates a significant amount of statistical reasoning and methods as natural applications of more standard college algebra topics. --From publisher description.

Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

Data Science for Software Engineering: Sharing Data and Models presents guidance and procedures for reusing data and models between projects to produce results that are useful and relevant. Starting with a background section of practical lessons and warnings for beginner data scientists for software engineering, this edited volume proceeds to identify critical questions of contemporary software engineering related to data and models. Learn how to adapt data from other organizations to local problems, mine privatized data, prune spurious information, simplify complex results, how to update models for new platforms, and more. Chapters share largely applicable experimental results discussed with the blend of practitioner focused domain expertise, with commentary that highlights the methods that are most useful, and applicable to the widest range of projects. Each chapter is written by a prominent expert and offers a state-of-the-art solution to an identified problem facing data scientists in software engineering. Throughout, the editors share best practices collected from their experience training software engineering students and practitioners to master data science, and highlight the methods that are most useful, and applicable to the widest range of projects. Shares the specific experience of leading researchers and techniques developed to handle data problems in the realm of software engineering Explains how to start a project of data science for software engineering as well as how to identify and avoid likely pitfalls Provides a wide range of useful qualitative and quantitative principles ranging from very simple to cutting edge research Addresses current challenges with software engineering data such as lack of local data, access issues due to data privacy, increasing data quality via cleaning of spurious chunks in data

Mathematical modelling is an important part of nuclear medicine. Therefore, several chapters of this book have been dedicated towards describing this topic. In these chapters, an emphasis has been put on describing the mathematical modelling of the radiation transport of photons and electrons, as well as on the transportation of radiopharmaceuticals between different organs and compartments. It also includes computer models of patient dosimetry. Two chapters of this book are devoted towards introducing the concept of biostatistics and radiobiology. These chapters are followed by chapters detailing dosimetry procedures commonly used in the context of diagnostic imaging, as well as patient-specific dosimetry for radiotherapy treatments. For safety reasons, many of the methods used in nuclear medicine and molecular imaging are tightly regulated. Therefore, this volume also highlights the basic principles for radiation protection. It discusses the process of how guidelines and regulations aimed at minimizing radiation exposure are determined and implemented by international organisations. Finally, this book describes how different dosimetry methods may be utilized depending on the intended target, including whole-body or organ-specific imaging, as well as small-scale to cellular dosimetry. This text will be an invaluable resource for libraries, institutions, and clinical and academic medical physicists searching for a complete account of what defines nuclear medicine. The most comprehensive reference available providing a state-of-the-art overview of the field of nuclear medicine Edited by a leader in the field, with contributions from a team of experienced medical physicists, chemists, engineers, scientists, and clinical medical personnel Includes the latest practical research in the field, in addition to explaining fundamental theory and the field's history

Introduction and background; Exploratory data analysis and graphics; Deterministic functions for ecological modeling; Probability and stochastic distributions for ecological modeling; Stochatsic simulation and power analysis; Likelihood and all that; Optimization and all that; Likelihood examples; Standar statistics revisited; Modeling variance; Dynamic models.

The end of this century has witnessed dramatic changes in morality, history and geography. These changes were felt throughout the world, and also across the entire gamut of professional concerns. Even relatively remote and seemingly insulated activities such as science and technology have experienced, and up to a point contributed to, these dramatic changes. This volume presents a series of views on the effect of these changes on science and technology, and more specifically, on the international diffusion of new technologies. These views come from a variety of fields, among them history and sociology of science, political science, information sciences, marketing. Yet, most authors share an interest in science policy studies which permeates this collection. It would be fair to say that this volume belongs to the intellectual domain known as STS, i. e. studies in Science, Technology and Society. The authors come from nine countries, and their contributions are expected to reflect this diversity. It is well known that the dominant lingua franca in the end of the 20th century is Broken English, with the possible exception of a minority of native English speakers some of whom fail to learn this new language. An attempt was therefore made throughout this volume to conform to a certain standard of English usage and, at the same time, to preserve the local flavour of expression, and the stylistic and cultural dimensions of each chapter.

While maintaining its focus on functions and graphs this book gives the adequately prepared algebra student the right start and flexible goals.