Methods for Data Analytics 1

Module code: EC2035

This module consists of two seemingly distinct parts: linear algebra and numerical programming in R. In order to do advanced numerical programming, one needs the knowledge of mathematical algorithm to code. This in turn requires fundamental knowledge in linear algebra in which much of the algorithm is cast.

Linear algebra is a very powerful tool for numerous disciplines including Statistics and Economics. Solid knowledge of linear algebra will be of considerable help with the subsequent module Data Analytics II and the third year core modules.

In the second half of the module, you will learn how to programme in R. Many of you will be familiar with spreadsheets such as Microsoft Excel to conduct data analysis. However, there is only so much you can do with spreadsheets. By learning to write loops which automate much of the tasks, you
will learn the enormous possibilities afforded by having skills to code, thereby telling the computer what you want it to do instead of being constrained by the capabilities built in clickable software packages.

You will learn not just to programme, but to be a smart programmer who can both minimise the script by writing loops wherever possible, and write them in a way such that it takes the least amount of time to do the computations and return the results.