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Author: Martina Bremer
Publisher:
ISBN: 9781621821120
Category : Bioinformatics
Languages : en
Pages : 0
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Book Description
Using R at the Bench: Step-by-Step Data Analytics for Biologists is a convenient bench-side handbook for biologists, designed as a handy reference guide for elementary and intermediate statistical analyses using the free/public software package known as "R." The expectations for biologists to have a more complete understanding of statistics are growing rapidly. New technologies and new areas of science, such as microarrays, next-generation sequencing, and proteomics, have dramatically increased the need for quantitative reasoning among biologists when designing experiments and interpreting results. Even the most routine informatics tools rely on statistical assumptions and methods that need to be appreciated if the scientific results are to be correct, understood, and exploited fully. Although the original Statistics at the Bench is still available for sale and has all examples in Excel, this new book uses the same text and examples in R. A new chapter introduces the basics of R: where to download, how to get started, and some basic commands and resources. There is also a new chapter that explains how to analyze next-generation sequencing data using R (specifically, RNA-Seq). R is powerful statistical software with many specialized packages for biological applications and Using R at the Bench: Step-by-Step Data Analytics for Biologists is an excellent resource for those biologists who want to learn R. This handbook for working scientists provides a simple refresher for those who have forgotten what they once knew and an overview for those wishing to use more quantitative reasoning in their research. Statistical methods, as well as guidelines for the interpretation of results, are explained using simple examples. Throughout the book, examples are accompanied by detailed R commands for easy reference.
Author: Martina Bremer
Publisher:
ISBN: 9781621821120
Category : Bioinformatics
Languages : en
Pages : 0
Get Book
Book Description
Using R at the Bench: Step-by-Step Data Analytics for Biologists is a convenient bench-side handbook for biologists, designed as a handy reference guide for elementary and intermediate statistical analyses using the free/public software package known as "R." The expectations for biologists to have a more complete understanding of statistics are growing rapidly. New technologies and new areas of science, such as microarrays, next-generation sequencing, and proteomics, have dramatically increased the need for quantitative reasoning among biologists when designing experiments and interpreting results. Even the most routine informatics tools rely on statistical assumptions and methods that need to be appreciated if the scientific results are to be correct, understood, and exploited fully. Although the original Statistics at the Bench is still available for sale and has all examples in Excel, this new book uses the same text and examples in R. A new chapter introduces the basics of R: where to download, how to get started, and some basic commands and resources. There is also a new chapter that explains how to analyze next-generation sequencing data using R (specifically, RNA-Seq). R is powerful statistical software with many specialized packages for biological applications and Using R at the Bench: Step-by-Step Data Analytics for Biologists is an excellent resource for those biologists who want to learn R. This handbook for working scientists provides a simple refresher for those who have forgotten what they once knew and an overview for those wishing to use more quantitative reasoning in their research. Statistical methods, as well as guidelines for the interpretation of results, are explained using simple examples. Throughout the book, examples are accompanied by detailed R commands for easy reference.
Author: Martina Bremer
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 188
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Book Description
This handbook is a convenient bench companion for biologists, designed as a handy reference guide for elementary and intermediate statistical analyses. Statistical methods most frequently used in publications and reports, as well as guidelines for the interpretation of results, are explained using simple examples with complete instructions for Excel.
Author: Hadley Wickham
Publisher: CRC Press
ISBN: 1498759807
Category : Mathematics
Languages : en
Pages : 476
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Book Description
An Essential Reference for Intermediate and Advanced R Programmers Advanced R presents useful tools and techniques for attacking many types of R programming problems, helping you avoid mistakes and dead ends. With more than ten years of experience programming in R, the author illustrates the elegance, beauty, and flexibility at the heart of R. The book develops the necessary skills to produce quality code that can be used in a variety of circumstances. You will learn: The fundamentals of R, including standard data types and functions Functional programming as a useful framework for solving wide classes of problems The positives and negatives of metaprogramming How to write fast, memory-efficient code This book not only helps current R users become R programmers but also shows existing programmers what’s special about R. Intermediate R programmers can dive deeper into R and learn new strategies for solving diverse problems while programmers from other languages can learn the details of R and understand why R works the way it does.
Author: Peter Dalgaard
Publisher: Springer Science & Business Media
ISBN: 0387790543
Category : Mathematics
Languages : en
Pages : 364
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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.
Author: Måns Thulin
Publisher: BoD - Books on Demand
ISBN: 9152701514
Category : Mathematics
Languages : en
Pages : 598
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Book Description
The past decades have transformed the world of statistical data analysis, with new methods, new types of data, and new computational tools. The aim of Modern Statistics with R is to introduce you to key parts of the modern statistical toolkit. It teaches you: - Data wrangling - importing, formatting, reshaping, merging, and filtering data in R. - Exploratory data analysis - using visualisation and multivariate techniques to explore datasets. - Statistical inference - modern methods for testing hypotheses and computing confidence intervals. - Predictive modelling - regression models and machine learning methods for prediction, classification, and forecasting. - Simulation - using simulation techniques for sample size computations and evaluations of statistical methods. - Ethics in statistics - ethical issues and good statistical practice. - R programming - writing code that is fast, readable, and free from bugs. Starting from the very basics, Modern Statistics with R helps you learn R by working with R. Topics covered range from plotting data and writing simple R code to using cross-validation for evaluating complex predictive models and using simulation for sample size determination. The book includes more than 200 exercises with fully worked solutions. Some familiarity with basic statistical concepts, such as linear regression, is assumed. No previous programming experience is needed.
Author: Jared P. Lander
Publisher: Addison-Wesley Professional
ISBN: 0134546997
Category : Computers
Languages : en
Pages : 1454
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Book Description
Statistical Computation for Programmers, Scientists, Quants, Excel Users, and Other Professionals Using the open source R language, you can build powerful statistical models to answer many of your most challenging questions. R has traditionally been difficult for non-statisticians to learn, and most R books assume far too much knowledge to be of help. R for Everyone, Second Edition, is the solution. Drawing on his unsurpassed experience teaching new users, professional data scientist Jared P. Lander has written the perfect tutorial for anyone new to statistical programming and modeling. Organized to make learning easy and intuitive, this guide focuses on the 20 percent of R functionality you’ll need to accomplish 80 percent of modern data tasks. Lander’s self-contained chapters start with the absolute basics, offering extensive hands-on practice and sample code. You’ll download and install R; navigate and use the R environment; master basic program control, data import, manipulation, and visualization; and walk through several essential tests. Then, building on this foundation, you’ll construct several complete models, both linear and nonlinear, and use some data mining techniques. After all this you’ll make your code reproducible with LaTeX, RMarkdown, and Shiny. By the time you’re done, you won’t just know how to write R programs, you’ll be ready to tackle the statistical problems you care about most. Coverage includes Explore R, RStudio, and R packages Use R for math: variable types, vectors, calling functions, and more Exploit data structures, including data.frames, matrices, and lists Read many different types of data Create attractive, intuitive statistical graphics Write user-defined functions Control program flow with if, ifelse, and complex checks Improve program efficiency with group manipulations Combine and reshape multiple datasets Manipulate strings using R’s facilities and regular expressions Create normal, binomial, and Poisson probability distributions Build linear, generalized linear, and nonlinear models Program basic statistics: mean, standard deviation, and t-tests Train machine learning models Assess the quality of models and variable selection Prevent overfitting and perform variable selection, using the Elastic Net and Bayesian methods Analyze univariate and multivariate time series data Group data via K-means and hierarchical clustering Prepare reports, slideshows, and web pages with knitr Display interactive data with RMarkdown and htmlwidgets Implement dashboards with Shiny Build reusable R packages with devtools and Rcpp Register your product at informit.com/register for convenient access to downloads, updates, and corrections as they become available.
Author:
Publisher: Dave Yarnell
ISBN:
Category :
Languages : en
Pages : 338
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Book Description
Author:
Publisher:
ISBN:
Category : Justices of the peace
Languages : en
Pages : 870
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Book Description
Author:
Publisher:
ISBN:
Category : Justices of the peace
Languages : en
Pages : 920
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Book Description
Author:
Publisher:
ISBN:
Category : Administrative law
Languages : en
Pages : 976
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Book Description
Special edition of the Federal Register, containing a codification of documents of general applicability and future effect ... with ancillaries.
