This module will be taught through practical classes in computer labs. Students will be expected to complete problem sheets to enforce learning. Relevant notes, examples and resources will be available on Blackboard.
Module Aim:
The aim of this module is to develop students' mathematical and statistical skills with a view to using these skills to analyse sports data. Students will be introduced to the areas of data visualisation, descriptive statistics and inferential statistics. The students will also be introduced to the use of statistical software for data analysis.
Learning Outcomes
On successful completion of this module the learner should be able to:
LO1
Describe basic concepts in statistics, data visualisation and data analysis.
LO2
Evaluate and apply key descriptive analysis techniques when carrying out analysis of sports data.
LO3
Evaluate and apply key inferential statistical techniques when carrying out analysis of sports data.
LO4
Solve well-formed problems by selecting the appropriate techniques and presenting the answer in a sporting context.
Pre-requisite learning
Module Recommendations
This is prior learning (or a practical skill) that is recommended before enrolment in this module.
No recommendations listed
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module.
No incompatible modules listed
Co-requisite Modules
No Co-requisite modules listed
Requirements
This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed.
No requirements listed
Module Content & Assessment
Indicative Content
Introduction to Statistics
Different data types, tabulation of data, and sampling. Measures of central tendency and dispersion including mean, median and standard deviation.
Data Visualisation
Description of different data visualisation techniques, their purpose and when they are suitable to use. Best practices in data visualisation.
Inferential Statistics
Application of correlation, linear regression and hypothesis testing to analysing sports data.
Computer Practicals
Application of theoretical material using relevant software.
Assessment Breakdown
%
Continuous Assessment
100.00%
Continuous Assessment
Assessment Type
Assessment Description
Outcome addressed
% of total
Assessment Date
Other
Learners will be required to demonstrate achievement of the learning outcomes through continuous assessment. This work may take the form of a project (individual/group), practical exam, presentation, case analysis, poster presentation but is not limited to these formats.
1,2,3,4
100.00
n/a
No Project
No Practical
No End of Module Formal Examination
SETU Carlow Campus reserves the right to alter the nature and timings of assessment