R is a development environment for statistical data analysis, but that is not all. It is a free software, distributed under the GNU GPL licence. R is emerging worldwide as the most used software for statistical, econometrics, and financial analysis as well as a tool for predictive analysis and machine learning. R features a very active community and an abundance of freely available packages that implement the most varied features. In short, it is a tool that should definitely be part of a data scientist’s toolkit! The course wants to first provide an introduction to the R environment and language, and then to address some specific issues such as the input and output of data in various formats, statistical analysis, and charting for visual analysis of the data.
- Introduction to the R environment and RStudio
- Basic functions
- Statistical functions
- Dealing with data in R: Input and output, working with vectors, matrices and data frames, built-in functions
- Programming with R: conditional expressions and loops
- Basic graphs: plots and histograms
- Working with data: how to manipulate data frames and the dplyr package
- Custom functions
- This is an introductory course
participants will benefit from a solid understanding of how to analyze data with statistical tools, and how to do it specifically with R.
This course is fundamental to go on studying more advanced data analytics techniques through the following courses: Predictive Analytics with R, Predictive Analytics with Rulex, Predictive Analytics with Azure Machine Learning e Fundamentals of Predictive Analytics: from theory to practice in two days
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