Engineering Your Future is an authoritative guide to the academic expectations and professional opportunities in engineering, a field that is both academically rigorous and creatively demanding. Today's engineering students are faced with endless career opportunities. This text clarifies thoseoptions and directs students down the path to a rewarding career in the engineering field.This concise and inexpensive version of the comprehensive edition contains the eleven most popular chapters from its parent text, offering the best option for instructors looking for a solid base from which to work while they incorporate outside projects or assignments.
Data Integration, Manipulation and Visualization of Phylogenetic Trees introduces and demonstrates data integration, manipulation and visualization of phylogenetic trees using a suite of R packages, tidytree, treeio, ggtree and ggtreeExtra. Using the most comprehensive packages for phylogenetic data integration and visualization, contains numerous examples that can be used for teaching and learning. Ideal for undergraduate readers and researchers with a working knowledge of R and ggplot2. Key Features: Manipulating phylogenetic tree with associated data using tidy verbs Integrating phylogenetic data from diverse sources Visualizing phylogenetic data using grammar of graphics
I Will Survive is the story of Gloria Gaynor, America's "Queen of Disco." It is the story of riches and fame, despair, and finally salvation. Her meteoric rise to stardom in the mid-1970s was nothing short of phenomenal, and hits poured forth that pushed her to the top of the charts, including "Honey Bee," "I Got You Under My Skin," "Never Can Say Goodbye," and the song that has immortalized her, "I Will Survive," which became a #1 international gold seller. With that song, Gloria heralded the international rise of disco that became synonymous with a way of life in the fast lane - the sweaty bodies at Studio 54, the lines of cocaine, the indescribable feeling that you could always be at the top of your game and never come down. But down she came after her early stardom, and problems followed in the wake, including the death of her mother, whose love had anchored the young singer, as well as constant battles with weight, drugs, and alcohol. While her fans always imagined her to be rich, her personal finances collapsed due to poor management; and while many envied her, she felt completely empty inside. In the early 1980s, sustained by her marriage to music publisher Linwood Simon, Gloria took three years off and reflected upon her life. She visited churches and revisited her mother's old Bible. Discovering the world of gospel, she made a commitment to Christ that sustains her to this day.
R Markdown: The Definitive Guide is the first official book authored by the core R Markdown developers that provides a comprehensive and accurate reference to the R Markdown ecosystem. With R Markdown, you can easily create reproducible data analysis reports, presentations, dashboards, interactive applications, books, dissertations, websites, and journal articles, while enjoying the simplicity of Markdown and the great power of R and other languages. In this book, you will learn Basics: Syntax of Markdown and R code chunks, how to generate figures and tables, and how to use other computing languages Built-in output formats of R Markdown: PDF/HTML/Word/RTF/Markdown documents and ioslides/Slidy/Beamer/PowerPoint presentations Extensions and applications: Dashboards, Tufte handouts, xaringan/reveal.js presentations, websites, books, journal articles, and interactive tutorials Advanced topics: Parameterized reports, HTML widgets, document templates, custom output formats, and Shiny documents. Yihui Xie is a software engineer at RStudio. He has authored and co-authored several R packages, including knitr, rmarkdown, bookdown, blogdown, shiny, xaringan, and animation. He has published three other books, Dynamic Documents with R and knitr, bookdown: Authoring Books and Technical Documents with R Markdown, and blogdown: Creating Websites with R Markdown. J.J. Allaire is the founder of RStudio and the creator of the RStudio IDE. He is an author of several packages in the R Markdown ecosystem including rmarkdown, flexdashboard, learnr, and radix. Garrett Grolemund is the co-author of R for Data Science and author of Hands-On Programming with R. He wrote the lubridate R package and works for RStudio as an advocate who trains engineers to do data science with R and the Tidyverse.
bookdown: Authoring Books and Technical Documents with R Markdown presents a much easier way to write books and technical publications than traditional tools such as LaTeX and Word. The bookdown package inherits the simplicity of syntax and flexibility for data analysis from R Markdown, and extends R Markdown for technical writing, so that you can make better use of document elements such as figures, tables, equations, theorems, citations, and references. Similar to LaTeX, you can number and cross-reference these elements with bookdown. Your document can even include live examples so readers can interact with them while reading the book. The book can be rendered to multiple output formats, including LaTeX/PDF, HTML, EPUB, and Word, thus making it easy to put your documents online. The style and theme of these output formats can be customized. We used books and R primarily for examples in this book, but bookdown is not only for books or R. Most features introduced in this book also apply to other types of publications: journal papers, reports, dissertations, course handouts, study notes, and even novels. You do not have to use R, either. Other choices of computing languages include Python, C, C++, SQL, Bash, Stan, JavaScript, and so on, although R is best supported. You can also leave out computing, for example, to write a fiction. This book itself is an example of publishing with bookdown and R Markdown, and its source is fully available on GitHub.
A princess thinks she was a bird, a coconut that cost a thousand rupees, and a shepherd with a bag of words...Kings and misers, princes and paupers, wise men and foolish boys, the funniest and oddest men and women come alive in this sparkling new collection of stories. The clever princess will only marry the man who can ask her a question she cannot answer; the orphan boy outwits his greedy uncles with a bag of ash; and an old couple in distress is saved by a magic drum. Sudha Murty's grandparents told her some of these stories when she was a child; others she heard from her friends from around the world. These delightful and timeless folktales have been her favourites for years, and she has recounted them many times over to the young people in her life. With this collection, they will be enjoyed by many more readers, of all ages. Age group of target audience is 8+.
This book describes EnvStats, a new comprehensive R package for environmental statistics and the successor to the S-PLUS module EnvironmentalStats for S-PLUS (first released in 1997). EnvStats and R provide an open-source set of powerful functions for performing graphical and statistical analyses of environmental data, bringing major environmental statistical methods found in the literature and regulatory guidance documents into one statistical package, along with an extensive hypertext help system that explains what these methods do, how to use these methods, and where to find them in the environmental statistics literature. EnvStats also includes numerous built-in data sets from regulatory guidance documents and the environmental statistics literature. This book shows how to use EnvStats and R to easily: * graphically display environmental data * plot probability distributions * estimate distribution parameters and construct confidence intervals on the original scale for commonly used distributions such as the lognormal and gamma, as well as do this nonparametrically * estimate and construct confidence intervals for distribution percentiles or do this nonparametrically (e.g., to compare to an environmental protection standard) * perform and plot the results of goodness-of-fit tests * compute optimal Box-Cox data transformations * compute prediction limits and simultaneous prediction limits (e.g., to assess compliance at multiple sites for multiple constituents) * perform nonparametric estimation and test for seasonal trend (even in the presence of correlated observations) * perform power and sample size computations and create companion plots for sampling designs based on confidence intervals, hypothesis tests, prediction intervals, and tolerance intervals * deal with non-detect (censored) data * perform Monte Carlo simulation and probabilistic risk assessment * reproduce specific examples in EPA guidance documents EnvStats combined with other R packages (e.g., for spatial analysis) provides the environmental scientist, statistician, researcher, and technician with tools to “get the job done!”
