R in a Nutshell


Book Description

Presents a guide to the R computer language, covering such topics as the user interface, packages, syntax, objects, functions, object-oriented programming, data sets, lattice graphics, regression models, and bioconductor.




R in a Nutshell


Book Description

Why learn R? Because it's rapidly becoming the standard for developing statistical software. R in a Nutshell provides a quick and practical way to learn this increasingly popular open source language and environment. You'll not only learn how to program in R, but also how to find the right user-contributed R packages for statistical modeling, visualization, and bioinformatics. The author introduces you to the R environment, including the R graphical user interface and console, and takes you through the fundamentals of the object-oriented R language. Then, through a variety of practical examples from medicine, business, and sports, you'll learn how you can use this remarkable tool to solve your own data analysis problems. Understand the basics of the language, including the nature of R objects Learn how to write R functions and build your own packages Work with data through visualization, statistical analysis, and other methods Explore the wealth of packages contributed by the R community Become familiar with the lattice graphics package for high-level data visualization Learn about bioinformatics packages provided by Bioconductor "I am excited about this book. R in a Nutshell is a great introduction to R, as well as a comprehensive reference for using R in data analytics and visualization. Adler provides 'real world' examples, practical advice, and scripts, making it accessible to anyone working with data, not just professional statisticians."




C# 10 in a Nutshell


Book Description

When you have questions about C# 10 or .NET 6, this best-selling guide has the answers you need. C# is a language of unusual flexibility and breadth, and with its continual growth, there's always so much more to learn. In the tradition of O'Reilly's Nutshell guides, this thoroughly updated edition is simply the best one-volume reference to the C# language available today. Organized around concepts and use cases, this comprehensive and complete reference provides intermediate and advanced programmers with a concise map of C# and .NET that also plumbs significant depths. Get up to speed on C#, from syntax and variables to advanced topics such as pointers, closures, and patterns Dig deep into LINQ, with three chapters dedicated to the topic Explore concurrency and asynchrony, advanced threading, and parallel programming Work with .NET features, including regular expressions, networking, assemblies, spans, reflection, and cryptography




The Nutshell Technique


Book Description

Veteran script consultant Jill Chamberlain discovered in her work that an astounding 99 percent of first-time screenwriters don’t know how to tell a story. These writers may know how to format a script, write snappy dialogue, and set a scene. They may have interesting characters and perhaps some clever plot devices. But, invariably, while they may have the kernel of a good idea for a screenplay, they fail to tell a story. What the 99 percent do instead is present a situation. In order to explain the difference, Chamberlain created the Nutshell Technique, a method whereby writers identify eight dynamic, interconnected elements that are required to successfully tell a story. Now, for the first time, Chamberlain presents her unique method in book form with The Nutshell Technique: Crack the Secret of Successful Screenwriting. Using easy-to-follow diagrams (“nutshells”), she thoroughly explains how the Nutshell Technique can make or break a film script. Chamberlain takes readers step-by-step through thirty classic and contemporary movies, showing how such dissimilar screenplays as Casablanca, Chinatown, Pulp Fiction, The Usual Suspects, Little Miss Sunshine, Juno, Silver Linings Playbook, and Argo all have the same system working behind the scenes, and she teaches readers exactly how to apply these principles to their own screenwriting. Learn the Nutshell Technique, and you’ll discover how to turn a mere situation into a truly compelling screenplay story.




Statistics in a Nutshell


Book Description

A clear and concise introduction and reference for anyone new to the subject of statistics.




Algorithms in a Nutshell


Book Description

Creating robust software requires the use of efficient algorithms, but programmers seldom think about them until a problem occurs. Algorithms in a Nutshell describes a large number of existing algorithms for solving a variety of problems, and helps you select and implement the right algorithm for your needs -- with just enough math to let you understand and analyze algorithm performance. With its focus on application, rather than theory, this book provides efficient code solutions in several programming languages that you can easily adapt to a specific project. Each major algorithm is presented in the style of a design pattern that includes information to help you understand why and when the algorithm is appropriate. With this book, you will: Solve a particular coding problem or improve on the performance of an existing solution Quickly locate algorithms that relate to the problems you want to solve, and determine why a particular algorithm is the right one to use Get algorithmic solutions in C, C++, Java, and Ruby with implementation tips Learn the expected performance of an algorithm, and the conditions it needs to perform at its best Discover the impact that similar design decisions have on different algorithms Learn advanced data structures to improve the efficiency of algorithms With Algorithms in a Nutshell, you'll learn how to improve the performance of key algorithms essential for the success of your software applications.




C# 9.0 in a Nutshell


Book Description

When you have questions about C# 9.0 or .NET 5, this best-selling guide has the answers you need. C# is a language of unusual flexibility and breadth, but with its continual growth there's so much more to learn. In the tradition of O'Reilly's Nutshell guides, this thoroughly updated edition is simply the best one-volume reference to the C# language available today. Organized around concepts and use cases, C# 9.0 in a Nutshell provides intermediate and advanced programmers with a concise map of C# and .NET that also plumbs significant depths. Get up to speed on C#, from syntax and variables to advanced topics such as pointers, records, closures, and patterns Dig deep into LINQ with three chapters dedicated to the topic Explore concurrency and asynchrony, advanced threading, and parallel programming Work with .NET features, including regular expressions, networking, spans, reflection, and cryptography




Statistical Mechanics in a Nutshell, Second Edition


Book Description

The essential introduction to modern statistical mechanics—now completely updated and expanded Statistical mechanics is one of the most exciting areas of physics today and has applications to subjects ranging from economics and social behavior to algorithmic theory and evolutionary biology. Statistical Mechanics in a Nutshell provides a self-contained introduction to this rapidly developing field. Starting with the basics of kinetic theory and requiring only a background in elementary calculus and mechanics, this concise book discusses the most important developments of recent decades and guides readers to the very threshold of today’s cutting-edge research. Features a new chapter on stochastic thermodynamics with an introduction to the thermodynamics of information—the first treatment of its kind in an introductory textbook Offers a more detailed account of numerical simulations, including simulated annealing and other accelerated Monte Carlo methods The chapter on complex systems now features an accessible introduction to the replica theory of spin glasses and the Hopfield theory of neural networks, with an emphasis on applications Provides a new discussion of defect-mediated transitions and their implications for two-dimensional melting An invaluable resource for graduate students and advanced undergraduates seeking a compact primer on the core ideas of statistical mechanics Solutions manual (available only to instructors)




Modern Data Science with R


Book Description

From a review of the first edition: "Modern Data Science with R... is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician). Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions. The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice.




Introductory Statistics with R


Book Description

This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded and contains the data sets. All examples are directly runnable and all graphics in the text are generated from the examples. The statistical methodology covered includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one-and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last four chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, and survival analysis.