These R training courses will allow you to make the most of this very powerful environment and language for statistical analysis and presentation. R is an open-source project which provides a full spectrum of statistical analysis. This includes linear and non-linear modelling, a full spectrum of classic statistical test, clustering and classification and time-series analysis. I will compile on Windows, Mac or Unix-based computers.
A key benefit of R is the ease with which attractive presentation quality plots and graphs can be produced. It offers users a wide and very flexible graphical capability. Helpfully graphs and plots can easily include mathematical symbols and formulas which are often difficult and time-consuming to add and manipulate.
Led by highly experienced R trainers with many years of experience in R, and more broadly in statistics, our hands-on courses mean that you will leave with plenty of practical experience.
These courses are focused on ensuring that we make you a faster and more relaxed R user.
Whether you are a beginner tackling R for the first time, or an advanced user, our courses are deliberately very hands-on. We believe that skills are developed through guided practice which reinforces learning and shows you how to apply what they are learning practically. Our R exercises are carefully chosen to emphasise the key aspects of each lesson.
R’s key strength is that is it so flexible and configurable. However, this flexibility can also be a two-edged sword. Beginners can struggle to know where to begin. By encouraging delegates to work independently in R we allow them to become familiar with how menus are structured and where different options are accessed.
If it would be more convenient for you we are also very happy to provide onsite R training at your offices.
R can be applied incredibly broadly. Wherever there are large amounts of data that needs to be analysed it is probably already being used. From academic institutions to large banks it’s flexibility and scalability are making it an increasingly popular choice.
For example, many quantitative analysts in finance use R as their main programming tool now. It can be used across the board, from importing and cleansing data through to analysis and data visualisation. Some institutions even use it for trading simulations and trading applications.
R is an implementation of the S language. S is a language that was developed for data analysis and visualisation, statistical modelling and simulation a couple of decades ago at Bell Labs. However, because S is a general purpose language both it and R can be used in applications far removed from data analysis.
R is an interpreted language and users interact with it via a command line interface. R is easily extensible through the user of libraries. The R community is well known for how active it’s contributions are meaning that a wide variety are on offer.
Two key benefits of R are that: