Review of the First Edition:The authors strive to reduce theory to a minimum, which makes it a self-learning text that is comprehensible for biologists, physicians, etc. who lack an advanced mathemati
This new edition includes some key topics relating to the latest version of MS Office, including use of the ribbon, current Excel file types, Dashboard, and basic Sharepoint integration. It shows how
This new edition includes some key topics relating to the latest version of MS Office, including use of the ribbon, current Excel file types, Dashboard, and basic Sharepoint integration. It shows how
Learn data science by doing data science! Data Science Using Python and R will get you plugged into the world’s two most widespread open-source platforms for data science: Python and R.Data scien
This book is designed to be a practical study in infectious disease dynamics. The book offers an easy to follow implementation and analysis of mathematical epidemiology. The book focuses on recent cas
Globally, a wide variety of organizations rely on ERDAS IMAGINE® daily, including local, state and national mapping agencies, transportation departments, defense organizations, engineering and utility
The book describes the emergence of big data technologies and the role of Spark in the entire big data stack. It compares Spark and Hadoop and identifies the shortcomings of Hadoop that have been over
The book presents the basic principles of sound graphical design and applies these principles to engaging examples using the graphical functions available in R. It offers a wide variety of graphical d
Statistical analysis is common in the social sciences, and among the more popular programs is R. This book provides a foundation for undergraduate and graduate students in the social sciences on how t
Statistical analysis is common in the social sciences, and among the more popular programs is R. This book provides a foundation for undergraduate and graduate students in the social sciences on how t
Exploratory Data Analysis Using R provides a classroom-tested introduction to exploratory data analysis (EDA) and introduces the range of "interesting" – good, bad, and ugly – features that can be fou
Presenting in depth discussions of various statistical models and methods needed for the analysis of medical, biological and biostatistics data, this book emphasizes the analysis of data when normal d
"This textbook will introduce exploratory data analysis (EDA) and will cover the range of interesting features we can expect to find in data. The book will also explore the practical mechanics of usin
Gain the basics of Ruby’s map, reduce, and select functions and discover how to use them to solve data-processing problems. This compact hands-on book explains how you can encode certain complex progr
Practical statistics is a powerful tool used frequently by agricultural researchers and graduate students involved in investigating experimental design and analysis. One of the most widely used statis
Bridging the gap between modern image processing practices by the scientific community at large and the world of geology and reflection seismology This book covers the basics of seismic exploration, w
This book will provide a thorough presentation of clinical trial methodology with detailed step-by-step illustrations on implementation in software R/SAS. The examples will be based on actual experien
This is a book about the scientific process and how it is applied to data in ecology. We will learn how to plan for data collection, how to assemble data, how to analyse data and finally how to presen
This is a book about the scientific process and how you apply it to data in ecology. You will learn how to plan for data collection, how to assemble data, how to analyze data and finally how to presen
For readers who may not be statisticians or data analysts, Sarmento and Costa explain how to analyze data using the Python and R languages. They have particularly in mind, students and researchers
This book addresses the difficulties experienced by wet lab researchers with the statistical analysis of molecular biology related data. The authors explain how to use R and Bioconductor for the analy
This practical book uses a step-by-step analysis of realistic examples to help students understand the theory and code for working with the R statistical language. With a comparison of both well-estab
