Postgraduate Course: Statistical Programming (MATH11176)
|School||School of Mathematics
||College||College of Science and Engineering
|Credit level (Normal year taken)||SCQF Level 11 (Postgraduate)
||Availability||Not available to visiting students
|Summary||The course will include extensive use of the high-level statistical programming language R, and aims to introduce the principles and use of computer programming with special focus on statistics using R.
* This course is available to Mathematics MSc students only. *
Introduction to R
Basic commands of R (arithmetic, vectors, logicals, simulation of random variables)
Data structures and data manipulation (characters, objects, lists, factors, dataframes, matrices)
Graphics in R (plots, lines and points, legends)
Functions and scripts (simple functions, for/while loops, if/ifelse conditional constructs)
Fast looping and efficient programming (vector arithmetic, vectors vs functions, apply, mapply)
Computer intensive techniques (sample topics: inverse/rejection/importance sampling, Monte Carlo integration, bootstrap, Gibbs sampling though the exact techniques may vary from year to year)
Entry Requirements (not applicable to Visiting Students)
||Other requirements|| * This course is available to Mathematics MSc students only. *
Course Delivery Information
|Academic year 2018/19, Not available to visiting students (SS1)
|Learning and Teaching activities (Further Info)
Lecture Hours 24,
Programme Level Learning and Teaching Hours 2,
Directed Learning and Independent Learning Hours
|Assessment (Further Info)
|Additional Information (Assessment)
||Coursework 100%, Examination 0%
|No Exam Information
On completion of this course, the student will be able to:
- Show familiarity with the principles of computer programming.
- Write efficient statistical functions and have experience of debugging.
- Demonstrate expertise in specialised software.
- Show appreciation of simulation based methods for statistical inference.
- Demonstrate expertise in widely used computationally intensive routines.
|Crawley. M. (2013). The R Book (2nd edition). Wiley.|
Venables, W. N. and Ripley, B. D., (2002). Modern Applied Statistics with S (4th edition). Springer
|Graduate Attributes and Skills
|Course organiser||Dr Gordon Ross
Tel: (0131 6)50 51111
|Course secretary||Miss Gemma Aitchison
Tel: (0131 6)50 9268