Using R for Data Management, Statistical Analysis, and Graphics by Nicholas J. Horton, Ken Kleinman

Using R for Data Management, Statistical Analysis, and Graphics Nicholas J. Horton, Ken Kleinman ebook
Publisher: CRC
ISBN: 1439827559, 9781439827550
Page: 296
Format: pdf

Passion runs high for the R programming language, which is changing the face of data analysis in business and academia. SAS does great data management and is really nice for large databases (100,000's of records or more). This course outline includes R introduction (including getting unstuck), Data Management, Graphics, and Statistical Analysis and Data Mining. John Chambers, now a consulting professor of statistics at Stanford University, drove much of the early S work at Bell Labs and talked with me at length about S and R. I also use it to write code (Making good progress but still learning) for managing and cleaning up hydrological and climate data (data aggregation, missing data, extracting indicators for testing etc.). Also, being an economics student, I was initially planning on doing my analysis in STATA, but I noticed on your blog that you use R, and apparently so does the rest of the statistics profession. I have recently started a PhD in Hydrology and have chosen R to perform the majority of my statistical analyses and to produce publication quality graphics. A huge part of “Data Science” is of course statistical analysis, so the two go hand-in-hand. SAS is a very successful private company still run by the original management. Every package seems to have a different strength (or weakness — if you cosndier SAS graphics) so knowing more is a pure good thing, in my opinion. Without question, R arrived as a result of the fine work done with S, but it's the rapid rise of R, .. Many people use R, an extensible, community-maintained language and environment for statistical computing and graphics. ACM San Francisco Bay Area Professional Chapter course.