>> Hello, everyone. In this segment I want to give a brief introduction to R and talk about some R background. R is a language and environment for statistical computing and graphics. R is used commonly by data scientists for prototyping and data science projects. Over the years the popularity of R has grown dramatically in industry and academics. Huge amounts of libraries and resources are available on the web. R is continually being refined and improved. R's functionality can be extended by many different packages. Okay, then. What is R for? R is for doing calculations, for data manipulation, for programming. R can create graphics. It has a large collection of field statistical tools. Furthermore R provides a wide variety of statistical techniques such as linear and non-linear modelling, classical statistical tests, time series analysis, classification and classing. Graphical techniques are highly extensible, as well. In the following weeks we will go through the data structures in the R language and introduce the statistical programming with R. In our course R Module 1 more information is provided for you to assist you in setting up your own R environment. R and RStudio are already installed in the computer labs for you, but seeing as how R is open source you are free to download, install and use R on your own computer, as well. You can easily find the websites for installing R and RStudio in our first module. There are some videos which are already provided to you in our first module, as well. The first two videos will help you to install R and RStudio either on a Windows computer or a Mac. Related to the videos provided to you an introduction to RStudio. I strongly recommend you to watch these videos before attending our lab section. This week's lab section will mainly cover managing the RStudio environment.