MA2501: Programming and Statistics
| School | Cardiff School of Mathematics |
| Department Code | MATHS |
| Module Code | MA2501 |
| External Subject Code | 100406 |
| Number of Credits | 10 |
| Level | L5 |
| Language of Delivery | English |
| Module Leader | Dr Andreas Artemiou |
| Semester | Autumn Semester |
| Academic Year | 2016/7 |
Outline Description of Module
This module will introduce the basics of programming in statistical software and will give students the opportunity to apply standard statistical methods to real data. The module will introduce basic principles of programming like Input/Output of data, defining elements of data in programming, creating small statistical functions for the program. It will also give the student the opportunity to see how basic statistical theory is applied in real datasets and recognize the different steps one takes in practice.
Prerequisite Modules: MA1501 Statistical Inference
Corequsite Modules: MA2500 Foundations of Probability and Statistics
On completion of the module a student should be able to
- Write small programs to perform statistical analysis.
- Do statistical analysis of real data
- Apply statistical concepts in data analysis.
How the module will be delivered
11 fifty-minute lectures
22 fifty-minute lab lectures
Some handouts will be provided in hard copy or via Learning Central, but students will be expected to take notes of lectures.
Students are also expected to undertake at least 50 hours private study including preparation of worked solutions for tutorial classes.
Skills that will be practised and developed
Working with Statistical Software
Modeling of large datasets
Visualization of large datasets
Transferable Skills:
Programming and data analysis skills.
How the module will be assessed
The in-course element of summative assessment is based on homework/lab activities with selected problems to complete where the students need to demonstrate their understanding of the theoretical basis of the methods discussed. Also, there will be a project where students will be given a programming problem and a real dataset to analyse using computing software.
The major component of summative assessment is the computer-lab based class test at the end of the module. This gives students the opportunity to demonstrate their overall achievement of learning outcomes. It also allows them to give evidence of the higher levels of knowledge and understanding required for above average marks.
Assessment Breakdown
| Type | % | Title | Duration(hrs) |
|---|---|---|---|
| Class Test | 60 | Programming And Statistics | 2 |
| Written Assessment | 15 | Coursework | N/A |
| Written Assessment | 25 | Project | N/A |
Syllabus content
- Introduction to a programming language for statisticians
- How to write basic programming blocks and functions
- Applying some univariate statistical analysis to data
- Applying some multivariate statistical analysis to data
- Data analysis
Essential Reading and Resource List
See Background Reading List
Background Reading and Resource List
Stowell, S., Using R for Statistics, Apress
Matloff, N., The Art of R Programming, No Starch Press
Dalgaard, P., Introductory Statistics with R, 2nd edition, Springer
Everitt, B. and Hothorn, T., An introduction to Applied Multivariate Analysis with R, Springer