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Software for data analysis: Programming with R

Software for data analysis: Programming with R. John Chambers

Software for data analysis: Programming with R
ISBN: 0387759352,9780387759357 | 514 pages | 13 Mb

Download Software for data analysis: Programming with R

Software for data analysis: Programming with R John Chambers
Publisher: Springer

R is quickly becoming the programming language for data analysis and statistics. R is a very popular and capable open source environment for data analysis and computation. This a brief guide to using R in collaborative, social ways. Data Management, Data Acquisition, and Knowledge Generation (25%). R (an implementation of S) is graphs (with R source code). Rather than cutting and pasting bits of code from a text editor into an interactive interpreter (as in Matlab, Python, or R) the notebook allows code and graphics to coexist in line with one another. Later, when I'm going Finally, the Mathematica programming language is pretty old. Bottom Line No, I would not recommend this to a friend. Popular graphics packages for R include lattice, ggplot2, and RGL or rggobi for more complex data visualization. R is the world's most popular language for developing statistical software: Archaeologists use it to track the spread of ancient civilizations, drug companies use it to discover which medications are safe and effective, and actuaries use it to assess. Use software tools such as Excel, Access, R, SAS, SPSS, SQL Server, Weka, Tableau, MapPoint, and PowerPoint to analyze data and present results. Here's Zen Koan: What's the value of a data analysis book with no data? For example, if I write some code for a data analysis I can have the plot of this data appear directly below the code itself in the notebook. (4 of 5 customers found this review helpful). For whatever reason, other statistical software (like Stata, which I also use) is not just easier to search for help for, but also tends to have more actually helpful help when you do find it. - You may also flag this review.

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