Using apply, sapply, lapply in R

This is an introductory post about using apply, sapply and lapply, best suited for people relatively new to R or unfamiliar with these functions. There is a part 2 coming that will look at density plots with ggplot, but first I thought I would go on a tangent to give some examples of the apply family, as they come up a lot working with R.

http://petewerner.blogspot.com/2012/12/using-apply-sapply-lapply-in-r.html

Posted by Imalsha Hewavidana

Why R? The pros and cons of the R language

Package ecosystem and graphics are strengths;
security and memory management are weaknesses.

Check this out!
http://www.infoworld.com/article/2940864/application-development/r-programming-language-statistical-data-analysis.html


Posted by Piyumi Dasanayaka

R for Multivariate Analysis

This booklet tells you how to use the R statistical software to carry out some simple multivariate analyses, with a focus on principal components analysis (PCA) and linear discriminant analysis (LDA).

http://little-book-of-r-for-multivariate-analysis.readthedocs.org/en/latest/src/multivariateanalysis.html


Posted by Isuru Dharmasena

Multiple Linear Regression (Fitting a model)

Linear regression is an approach for modeling the relationship between a scalar dependent variable y and one or more explanatory variables (or independent variables) denoted x. The case of one explanatory variable is called simple linear regression. For more than one explanatory variable, the process is called multiple linear regression.

http://www.statmethods.net/stats/regression.html

Posted by Chathuri Aththanayake