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

Now in its Fifth Edition, this much-loved text offers theoretical and philosophical depth as well as insights into practice. The text covers the entire research process in an accessible way and provides critical, thoughtful treatment of important issues like ethics and politics, making it an invaluable companion for any business and management student New to the Fifth Edition: Expanded to include examples from across business and management including Marketing, International Business and Psychology Up-to-date, international examples and cases from a range of countries Introductory chapter looks at writing proposals in detail Chapter on the literature review now includes how to critically review Move towards new technologies and social media including discussion of wikis and cloud sourcing Improved structure and flow, with three chapters on qualitative methods and three on quantitative methods Additional practical exercises which are linked to key research tasks throughout The companion website (https://edge.sagepub.com/easterbysmith) offers a wealth of resources for both lecturers and students including, for lecturers, an instructor′s manual and PowerPoint slides and, for students, author podcasts, journal articles, web links, MCQs, datasets and a glossary.

A groundbreaking introduction to vectors, matrices, and least squares for engineering applications, offering a wealth of practical examples.

This introduction to computational geometry focuses on algorithms. Motivation is provided from the application areas as all techniques are related to particular applications in robotics, graphics, CAD/CAM, and geographic information systems. Modern insights in computational geometry are used to provide solutions that are both efficient and easy to understand and implement.

Rigorous introduction is simple enough in presentation and context for wide range of students. Symbolizing sentences; logical inference; truth and validity; truth tables; terms, predicates, universal quantifiers; universal specification and laws of identity; more.

Learn How to Program with Swift 5.5!Swift is the easiest way to get started developing on Apple's platforms: iOS, iPadOS, macOS, watchOS and tvOS. In this book, you'll learn the basics of Swift from getting started with playgrounds to simple operations to building your own types. Everything you'll learn is platform-neutral; you'll have a firm understanding of Swift by the end of this book, and you'll be ready to move on to whichever app platform you're interested in.Who This Book Is For:This book is for complete beginners to Swift. No prior programming experience is necessary!Topics Covered in The Swift ApprenticePlayground basics: Learn about the coding environment where you can quickly and easily try out your code as you learn.Basic types: Numbers and strings are the basic kinds of data in any app - learn how to use them in Swift.Flow control: Your code doesn't always run straight through - learn how to use conditions and decide what to do.Functions: Group your code together into reusable chunks to run and pass around.Collection types: Discover the many ways Swift offers to store and organize data into collections.Protocols & protocol-oriented programming: Define protocols to make your code more interface-based and compositional.Advanced topics: Learn how to create custom operators, organize your code, write tests, manage memory, serialize your types, concurrency and so much more.After reading this book and completing your Swift apprenticeship by working through the included exercises and challenges, you'll be ready to take on app development on the platform of your choice!

Master the Shiny web framework—and take your R skills to a whole new level. By letting you move beyond static reports, Shiny helps you create fully interactive web apps for data analyses. Users will be able to jump between datasets, explore different subsets or facets of the data, run models with parameter values of their choosing, customize visualizations, and much more. Hadley Wickham from RStudio shows data scientists, data analysts, statisticians, and scientific researchers with no knowledge of HTML, CSS, or JavaScript how to create rich web apps from R. This in-depth guide provides a learning path that you can follow with confidence, as you go from a Shiny beginner to an expert developer who can write large, complex apps that are maintainable and performant. Get started: Discover how the major pieces of a Shiny app fit together Put Shiny in action: Explore Shiny functionality with a focus on code samples, example apps, and useful techniques Master reactivity: Go deep into the theory and practice of reactive programming and examine reactive graph components Apply best practices: Examine useful techniques for making your Shiny apps work well in production