R for data analysis is a wide-ranging course, covers all aspects of R from basics, through to sophisticated graphics, advanced programming techniques and data mining algorithms. It has strong business focus, illustrating how analytical findings can be used for organisational planning purposes.
Module 1- Introduction to R Data loading, cleaning and transformation:
Install R, install R Studio and learn to use R with its great statistical functionality. Introduction and revision of basic statistics.
Loading data from Excel, SQL, XML and the web, using SQL notation to query R data, cleaning and transforming your data (missing values, recoding and converting variables, creating new variables), merging and sampling data.
Module 3: Sampling and the simple principles of experimental design
Data Processing: Data Processing tips
Module 4: Design of experiments and using analysis of variance (ANOVA)
Module 2 - Programming
We learn the basics of procedural programming – variables, control structures and writing simple functions – before moving on to building more sophisticated functions geared to manipulating large datasets.