Environmental Statistics
Автор: Группа авторов
Год издания: 0000
In modern society, we are ever more aware of the environmental issues we face, whether these relate to global warming, depletion of rivers and oceans, despoliation of forests, pollution of land, poor air quality, environmental health issues, etc. At the most fundamental level it is necessary to monitor what is happening in the environment – collecting data to describe the changing scene. More importantly, it is crucial to formally describe the environment with sound and validated models, and to analyse and interpret the data we obtain in order to take action. Environmental Statistics provides a broad overview of the statistical methodology used in the study of the environment, written in an accessible style by a leading authority on the subject. It serves as both a textbook for students of environmental statistics, as well as a comprehensive source of reference for anyone working in statistical investigation of environmental issues. Provides broad coverage of the methodology used in the statistical investigation of environmental issues. Covers a wide range of key topics, including sampling, methods for extreme data, outliers and robustness, relationship models and methods, time series, spatial analysis, and environmental standards. Includes many detailed practical and worked examples that illustrate the applications of statistical methods in environmental issues. Authored by a leading authority on environmental statistics.
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
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.
Environmental texts: Reading and translation
Автор: Е. Д. Андреева
Год издания:
Учебное пособие содержит основные теоретические сведения о переводе научно-публицистических текстов, оригинальные и адаптированные тексты на английском и русском языках.
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
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.