Posted by **interes** at June 30, 2014

English | 2010 | ISBN: 1584885742 | 202 pages | PDF | 4 MB

Adopting a unifying theme based on maximum statistics, Multiple Comparisons Using R describes the common underlying theory of multiple comparison procedures through numerous examples. It also presents a detailed description of available software implementations in R.

Posted by **arundhati** at Sept. 22, 2013

2010 | ISBN: 1584885742 | 202 pages | PDF | 4,1 MB

Posted by **Specialselection** at March 23, 2012

English | 2010-07-27 | ISBN: 1584885742 | 202 pages | PDF | 2.9 mb

Posted by **roxul** at Nov. 29, 2016

English | ISBN: 3319443259 | 2016 | 262 pages | PDF | 5 MB

Posted by **insetes** at Nov. 25, 2016

2012 | 1036 Pages | ISBN: 1439809755 | PDF | 131 MB

Posted by **rotten comics** at Nov. 25, 2016

2004 | ISBN: 1584884509 | English | 432 pages | PDF | 3 MB

Posted by **DZ123** at Nov. 13, 2016

English | 2014 | ISBN: 1439873437 | PDF | pages: 283 | 2.0 mb

Posted by **insetes** at Nov. 6, 2016

2014 | 287 Pages | ISBN: 1439873437 | PDF | 2 MB

Posted by **house23** at Nov. 5, 2016

MP4 | AVC 470kbps | English | 1280x720 | 30fps | 17 hours | AAC stereo 59kbps | 2.68 GB

This course ensure quick learning in a simplified way. It explains the most important aspects of working on data and conduct analysis through example. You will start by learning how to install and navigate R studio. Learn Data/Object Types and Operations, Importing into R, and Loops and Conditions. you will be introduced to the use of R in Analytics, where you will learn a little about each object type in R and use that in Data Mining/Analytical Operations. learn the use of R in Statistics, using R to evaluate Descriptive Statistics, Probability Distributions, Hypothesis Testing, Linear Modeling, Generalized Linear Models, Non-Linear Regression, and Trees. Learn to create 2-dimensional Univariate and Multi-variate plots.

Posted by **leonardo78** at Oct. 30, 2016

English | 2006-02-17 | ISBN: 1584885394 | 269 pages | PDF | 1,4 mb

R is dynamic, to say the least. More precisely, it is organic, with new functionality and add-on packages appearing constantly. And because of its open-source nature and free availability, R is quickly becoming the software of choice for statistical analysis in a variety of fields.