Найти книгу: "Statistics for Spatial Data"


Statistics for Spatial Data Statistics for Spatial Data

Автор: Группа авторов

Год издания: 0000

The Wiley Classics Library consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. Spatial statistics – analyzing spatial data through statistical models – has proven exceptionally versatile, encompassing problems ranging from the microscopic to the astronomic. However, for the scientist and engineer faced only with scattered and uneven treatments of the subject in the scientific literature, learning how to make practical use of spatial statistics in day-to-day analytical work is very difficult. Designed exclusively for scientists eager to tap into the enormous potential of this analytical tool and upgrade their range of technical skills, Statistics for Spatial Data is a comprehensive, single-source guide to both the theory and applied aspects of spatial statistical methods. The hard-cover edition was hailed by Mathematical Reviews as an «excellent book which will become a basic reference.» This paper-back edition of the 1993 edition, is designed to meet the many technological challenges facing the scientist and engineer. Concentrating on the three areas of geostatistical data, lattice data, and point patterns, the book sheds light on the link between data and model, revealing how design, inference, and diagnostics are an outgrowth of that link. It then explores new methods to reveal just how spatial statistical models can be used to solve important problems in a host of areas in science and engineering. Discussion includes: Exploratory spatial data analysis Spectral theory for stationary processes Spatial scale Simulation methods for spatial processes Spatial bootstrapping Statistical image analysis and remote sensing Computational aspects of model fitting Application of models to disease mapping Designed to accommodate the practical needs of the professional, it features a unified and common notation for its subject as well as many detailed examples woven into the text, numerous illustrations (including graphs that illuminate the theory discussed) and over 1,000 references. Fully balancing theory with applications, Statistics for Spatial Data, Revised Edition is an exceptionally clear guide on making optimal use of one of the ascendant analytical tools of the decade, one that has begun to capture the imagination of professionals in biology, earth science, civil, electrical, and agricultural engineering, geography, epidemiology, and ecology.
Applied Statistics and the SAS Programming Language Applied Statistics and the SAS Programming Language

Автор: Ronald P. Cody, Jeffrey K. Smith

Год издания: 

This book is intended to provide the applied researcher with the capacity to perform statistical analyses with SAS software without wading through pages of technical documentation. The researcher is provided with the necessary SAS statements to run programs for most of the commonly used statistics, explanations of the computer output, interpretations of results, and examples of how to construct tables and write up results for reports and journal articles.

Статистика туризма = Tourism statistics Статистика туризма = Tourism statistics

Автор: Татьяна Карманова

Год издания: 

Раскрыты основополагающие принципы и сущность статистики туризма. Детально рассмотрены предмет, задачи и система показателей статистики туризма, методология статистической оценки и анализ развития международного и внутреннего туризма, а также современные направления развития статистики туризма в мире и России. Соответствует Федеральному государственному образовательному стандарту высшего профессионального образования третьего поколения. Для студентов бакалавриата, магистратуры, аспирантов, преподавателей высших учебных заведений, слушателей системы послевузовского образования, а также бухгалтеров, аудиторов, экономистов, менеджеров предприятий туристской индустрии.

Прогнозное моделирование в IBM SPSS Statistics, R и Python. Метод деревьев решений и случайный лес Прогнозное моделирование в IBM SPSS Statistics, R и Python. Метод деревьев решений и случайный лес

Автор: Артем Груздев

Год издания: 

Данная книга представляет собой практическое руководство по применению метода деревьев решений и случайного леса для задач сегментации, классификации и прогнозирования. Каждый раздел книги сопровождается практическим примером. Кроме того, книга содержит программный код SPSS Syntax, R и Python, позволяющий полностью автоматизировать процесс построения прогнозных моделей. Автором обобщены лучшие практики использования деревьев решений и случайного леса от таких компаний, как Citibank N.A., Transunion и DBS Bank. Издание будет интересно маркетологам, риск-аналитикам и другим специалистам, занимающимся разработкой и внедрением прогнозных моделей.

SPSS Statistics for Data Analysis and Visualization SPSS Statistics for Data Analysis and Visualization

Автор: Andrew Wheeler

Год издания: 

Dive deeper into SPSS Statistics for more efficient, accurate, and sophisticated data analysis and visualization SPSS Statistics for Data Analysis and Visualization goes beyond the basics of SPSS Statistics to show you advanced techniques that exploit the full capabilities of SPSS. The authors explain when and why to use each technique, and then walk you through the execution with a pragmatic, nuts and bolts example. Coverage includes extensive, in-depth discussion of advanced statistical techniques, data visualization, predictive analytics, and SPSS programming, including automation and integration with other languages like R and Python. You'll learn the best methods to power through an analysis, with more efficient, elegant, and accurate code. IBM SPSS Statistics is complex: true mastery requires a deep understanding of statistical theory, the user interface, and programming. Most users don't encounter all of the methods SPSS offers, leaving many little-known modules undiscovered. This book walks you through tools you may have never noticed, and shows you how they can be used to streamline your workflow and enable you to produce more accurate results. Conduct a more efficient and accurate analysis Display complex relationships and create better visualizations Model complex interactions and master predictive analytics Integrate R and Python with SPSS Statistics for more efficient, more powerful code These «hidden tools» can help you produce charts that simply wouldn't be possible any other way, and the support for other programming languages gives you better options for solving complex problems. If you're ready to take advantage of everything this powerful software package has to offer, SPSS Statistics for Data Analysis and Visualization is the expert-led training you need.

Style and Statistics. The Art of Retail Analytics Style and Statistics. The Art of Retail Analytics

Автор: Brittany Bullard

Год издания: 

A non-technical guide to leveraging retail analytics for personal and competitive advantage Style & Statistics is a real-world guide to analytics in retail. Written specifically for the non-IT crowd, this book explains analytics in an approachable, understandable way, and provides examples of direct application to retail merchandise management, marketing, and operations. The discussion covers current industry trends and emerging-standard processes, and illustrates how analytics is providing new solutions to perennial retail problems. You'll learn how to leverage the benefits of analytics to boost your personal career, and how to interpret data in a way that's useful to the average end business user or shopper. Key concepts are detailed in easy-to-understand language, and numerous examples highlight the growing importance of understanding analytics in the retail environment. The power of analytics has become apparent across industries, but it's left an especially indelible mark on retail. It's a complex topic, but you don't need to be a data scientist to take advantage of the opportunities it brings. This book shows you what you need to know, and how to put analytics to work with retail-specific applications. Learn how analytics can help you be better at your job Dig deeper into the customer's needs, wants, and dreams Streamline merchandise management, pricing, marketing, and more Find solutions for inefficiencies and inaccuracies As the retail customer evolves, so must the retail industry. The retail landscape not only includes in-store but also website, mobile site, mobile apps, and social media. With more and more competition emerging on all sides, retailers need to use every tool at their disposal to create value and gain a competitive advantage. Analytics offers a number of ways to make your company stand out, whether it's through improved operations, customer experience, or any of the other myriad factors that build a great place to shop. Style & Statistics provides an analytics primer with a practical bent, specifically for the retail industry.