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.

Course Content

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.

Module 5: Design of experiments and using Regression
Module 6: Proportions, Chi squared and Goodness of Fit
Module 7: Surveys design and analysis
Module 8: Advanced plotting in R
Module 9: Advanced and some Multivariate Techniques

4 – 6 weeks

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