Spatial Data Analysis

The definitive guide to bringing accuracy to measurement, updated and supplemented Adjustment Computations is the classic textbook for spatial information analysis and adjustment computations, providi

Applied Spatial Data Analysis with R, second edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of intere

This book takes both a retrospective and prospective view of the field of spatial analysis by combining selected reprints of classic articles by Arthur Getis with current observations by leading exper

Assuming no prior knowledge of R, Spatial Data Analysis in Ecology and Agriculture Using R provides practical instruction on the use of the R programming language to analyze spatial data arising from

The availability of spatial databases and widespread use of geographic information systems has stimulated increasing interest in the analysis and modelling of spatial data. Spatial data analysis focus

the complete guide to adjusting for measurement error—expanded and updated no measurement is ever exact. Adjustment Computations updates a classic, definitive text on surveying with the late

This book takes both a retrospective and prospective view of the field of spatial analysis by combining selected reprints of classic articles by Arthur Getis with current observations by leading exper

What is the shortest route between one point and another in a road network? Where is the incidence of disease the highest? How does rainfall correlate with altitude? How does the concentration of a po

Understanding spatial statistics requires tools from applied and mathematical statistics, linear model theory, regression, time series, and stochastic processes. It also requires a mindset that focuse

Integrating a discussion of the application of quantitative methods with practical examples, this book explains the philosophy of the new quantitative methodologies and contrasts them with the methods

A comprehensive, data-driven introduction to modern spatial data analysis, a field which is playing an increasing role in many areas of research and policy making. Provides full explanations for a wid

Within both the social and environmental sciences, much of the data collected is within a spatial context and requires statistical analysis for interpretation. The purpose of this book is to describe current methods for the analysis of spatial data. Methods described include data description, map interpolation, and exploratory and explanatory analyses. The book also examines spatial referencing, and methods for detecting problems, assessing their seriousness and taking appropriate action are discussed. This is an important text for any discipline requiring a broad overview of current theoretical and applied work for the analysis of spatial data sets. It will be of particular use to research workers and final year undergraduates in the fields of geography, environmental sciences and social sciences.

Spatial Data Analysis in Ecology and Agriculture Using R, 2nd Edition provides practical instruction on the use of the R programming language to analyze spatial data arising from research in ecology,

Applications of spatial data, coupled with geographic information systems, are finding increasing use in the disciplines of geography and geology, as well as environmental science, ecology, epidemiolo

Validation is a critical component to programming clinical trial analysis. Essential to effective validation is the programmer's understanding of the data with which they'll be working. If you don't u

A comprehensive and current introduction to the fundamentals of regression analysisIntroduction to Linear Regression Analysis, 6th Edition is the most comprehensive, fulsome, and current examination of the foundations of linear regression analysis. Fully updated in this new sixth edition, the distinguished authors have included new material on generalized regression techniques and new examples to help the reader understand retain the concepts taught in the book.The new edition focuses on four key areas of improvement over the fifth edition: New exercises and data setsNew material on generalized regression techniquesThe inclusion of JMP software in key areasCarefully condensing the text where possibleIntroduction to Linear Regression Analysis skillfully blends theory and application in both the conventional and less common uses of regression analysis in today's cutting-edge scientific research. The text equips readers to understand the basic principles needed to apply regression model-b

Spatial Thinking in Environmental Contexts: Maps, Archives, and Timelines cultivates the spatial thinking "habit of mind" as a critical geographical view of how the world works, including how environm

Gain insight into essential data science skills in a holistic manner using data engineering and associated scalable computational methods. This book covers the most popular Python 3 frameworks for bot

Based on rare first-hand historical data, Wang Ke presents the analysis of the East Turkestan from the perspective of Islamic social structure, the origin and evolution of thoughts on national revolut

A valuable new edition of a standard referenceThe use of statistical methods for categorical data has increased dramatically, particularly for applications in the biomedical and social sciences. An In

This practical guide in Eviews is aimed at practitioners and students in business, economics, econometrics, and finance. It uses a step-by-step approach to equip readers with a toolkit that enables them to make the most of this widely used econometric analysis software. Statistical and econometrics concepts are explained visually with examples, problems, and solutions.Developed by economists, the Eviews statistical software package is used most commonly for time-series oriented econometric analysis. It allows users to quickly develop statistical relations from data and then use those relations to forecast future values of the data. The package provides convenient ways to enter or upload data series, create new series from existing ones, display and print series, carry out statistical analyses of relationships among series, and manipulate results and output. This highly hands-on resource includes more than 200 illustrative graphs and tables and tutorials throughout. Abdulkader Alja

Data Science and Analytics with Python is designed for practitioners in data science and data analytics in both academic and business environments. The aim is to present the reader with the main conce

In an era where many believe Big Data has rendered human perception and observation 'old-school' or pass', Martin Lindstrom shows that mining and matching technological data with up-close psychologica

Use real data, and become a pro at using Excel for statistical analysis! Designed for users already familiar with Excel and basic computer operations, this Second Edition of Neil J. Salkind’s Excel St

Proven strategies for implementing the right data warehouse and business intelligence solutions for current and future business needs In The Data Warehouse Mentor: Practical Data Warehouse and Busines

Master Oracle Data Guard 11g Provide superior data protection, availability, and disaster recovery using the tested techniques in this Oracle Press guide. Cowritten by a team of Oracle experts, Oracl

With an increasing concern of personal data privacy in Hong Kong and around the world, the Office of the Privacy Commissioner for Personal Data (PCPD), Hong Kong publishes this third edition of Personal Data (Privacy) Law in Hong Kong: A Practical Guide on Compliance to provide practical guidance on the law of privacy, and the ways to protect personal data in everyday life.This third edition will guide readers through the recent developments of personal data privacy in the local, regional and global contexts with updates on recent Administrative Appeals Board and Court decisions, and investigation reports and materials from the PCPD. In addition, some most-concerned issues are discussed, such as ethical development and use of AI, the collection and use of personal data by employers during COVID-19, data protection under work-from-home arrangements, data security measures for ICT systems, guidelines on doxxing offences and data breach handling. This book will certainly provide readers a

This book illustrates and explains the key concepts of business data analytics from scratch, tackling the day-to-day challenges of a business data analyst. It provides you with all the professional tools you need to predict online shop sales, to conduct A/B tests on marketing campaigns, to generate automated reports with PowerPoint, to extract datasets from Wikipedia, and to create interactive analytics Web apps. Alongside these practical projects, this book provides hands-on coding exercises, case studies, the essential programming tools and the CRISP-DM framework which you'll need to kickstart your career in business data analytics.The different chapters prioritize practical understanding over mathematical theory, using realistic business data and challenges of the Junglivet Whisky Company to intuitively grasp key concepts and ideas. Designed for beginners and intermediates, this book guides you from business data analytics fundamentals to advanced techniques, covering a large number