Introduction -- Why use R for your statistical work? -- Whom is this book for? -- My own background -- Getting started -- How to run R -- A first R session -- Introduction to functions -- Preview of ...

R is the most popular language used for data analysis, modelling and visualisation. It is great for linear and non-linear models, parametric and non-parametric tests, clustering and time-series models ...

For those who might be wondering, the programming language was created by Ross Ihaka and Robert Gentleman in 1993. Furthermore, note that most of the R libraries are written using R, but for others, C ...

Do you want to improve your R skills? Here are my favorite R language resources for users at any level. [This story is part of Computerworld’s “Beginner’s guide to R.” You’ll find links to the whole ...

Combining multiple datasets, whether by stacking or joining, is commonly necessary as is changing the shape of data. The plyr and reshape2 packages offer good functions for accomplishing this in ...

Do you have some data with geolocation information that you want to map? You may not think of R when you’re looking for a GIS platform, but new packages and standards have helped make the R ...

Predictive analysis refers to the use of historical data and analyzing it using statistics to predict future events. It takes place in seven steps, and these are: defining the project, data collection ...