CSC-20053 - Statistical Techniques for Data Analytics

Coordinator: Ka-Po Lam Room: CR022 Tel: +44 1782 7 34110

Lecture Time: See Timetable...

Level: Level 5

Credits: 15

Study Hours: 150

School Office: 01782 733075

Programme/Approved Electives for 2020/21

None

Available as a Free Standing Elective

Co-requisites

None

Prerequisites

None

Barred Combinations

None

Description for 2020/21

The module equips learners with the knowledge of a variety of tools and statistical techniques to enable them to make sense of the exponential growth of big data. The learners will understand advanced analytics and statistical modelling techniques and evaluate their applicability for different types of problems.

Aims

The module aims to equip learners with the knowledge of a variety of tools and statistical techniques that enable them to deal with the analysis of large volumes of data.
The learners will be able to choose and apply analytics and statistical modelling techniques appropriate to different types of problems.

Intended Learning Outcomes

identify and apply machine learning methods in the context of statistical analysis of data: 1,2
apply statistical data analytics techniques using an advanced specialist programming language (e.g. R, Python, Matlab): 1,2
contrast the options of storing, managing and manipulating large volumes of data in the context of business organisations: 1,2
choose and apply an appropriate statistical approach to extract information from a set of data, typically available in a modern business organisation: 1,2

Study hours

20 hours workshops/tutorials (supported online and in block release)
20 hours online lectures
108 hour independent learning
2 hour class-test (during block release)

School Rules

None

Description of Module Assessment

1: Assignment weighted 50%
Written report
A report (maximum 2000 words) on the accessing, storage, manipulation and analysis of data available from an internet based data repository. Code and analysed data will be submitted as an appendix.

2: Class Test weighted 50%
A 2-hour open book class test about statistical data analysis techniques.
The class test contains a set of questions. The learners will have to answer a minimum subset of these questions. The questions cover book work material covered during the online lectures (e.g. definitions, comparisons of concepts) and data analysis algorithms, including application and modification of such algorithms and advanced aspects of these algorithms. The class test is a mixed test.

CSC-20053 - Module Specification School of Computing and Mathematics Faculty of Natural Sciences

CSC-20053 - Module Specification
School of Computing and Mathematics
Faculty of Natural Sciences