Introduction to Statistical Programming

Data Science Campus and Analysis Function logos.

To switch between light and dark modes, use the toggle in the top right

1 Introduction

Landing page for the Introduction to Statistical Programming Pathway training pathway.

Profile Description: Limited or no coding background, need to read code, make small changes in a pipeline and/or create visualisations.

It is essential that you have frequent opportunities to practice what you have learnt from the courses in this pathway.

2 Introduction to Python/R

This will cover basic concepts and given you the confidence to work independently in the programming language you choose. No prior coding or statistical knowledge is assumed, however we recommend you are confident using basic computer software.

Complete one of either:

3 Data Visualisation

Data visualisation is an interdisciplinary field that deals with the graphic representation of data. Visualising data makes it easier to spot trends, patterns, interpret results and speeds up the decision-making process.

Complete one of either:

4 Statistics in Python/R

These courses introduce the basics of carrying out a statistical analysis in your chosen language. It covers exploratory data analysis and constructing and interpreting linear and generalised linear models.

5 Effective Programming

There are some general principles which you can follow in order to improve your coding skills and enable others to read it, offer feedback or even make contributions. As the writing of code becomes more crucial to analysis, the need for well structured code has increased.

Complete Best Practice in Programming to gain an understanding of what clean code is, the importance of writing it and implementation in your own work.

Another key component in well written, reproducible code is the idea of “modular” design. This is the splitting up of code into different units which work separately from the rest of the code. Complete Modular Programming to learn important concepts relating to modular code, how to convert code to functions and modules in either R or Python.