The aim of this module is to develop skills needed to process information and provide an understanding of statistical methods to analyse the resulting data. The techniques studied will enable data collection from a range of sources, including files and the web. The module will cover Python modules that can easily manipulate and convert information to extract data. Statistics to describe collections of data will be studied, along with basic methods to derive correlations and test simple hypotheses.

1. Use Python to extract, manipulate, store and analyse information from a range of sources.
2. Understand statistical methods to apply to data
3. Understand static visualisations of data
4. Create static visualisations of data

Modules will be delivered through blended learning. You will be guided through learning activities appropriate to your module, which may include: • on-line resources that you work through at your own pace (e.g. videos, web resources, e-books, quizzes), • on-line interactive sessions to work with other students and staff (e.g. discussions, live streaming of presentations, live-coding, team meetings) • face to face small group sessions (e.g. help classes, feedback sessions)

Retrieve and manipulate data

Statistical data analysis

Create static visualisations of data

A blend of assessment types which may include coursework and portfolio assessments, class tests, and/or formal examinations.

Python modules for data processing, for example:

pandas

statsmodels

scipy

Statistical methods

Linear regression

Linear correlation

Hypothesis testing

Visualisation

Matplotlib

Doing Data Science: Straight Talk from the Frontline, Cathy O'Neil and Rachel Schutt (ISBN-10: 1449358659)

Python for Data Analysis, Wes McKinney (ISBN 10: 1449319793)