| Module Code | ST8002 |
| Module Name | Implementing statistical methods in R |
| ECTS Weighting[1] | 5 ECTS |
| Semester taught | Semester 1 |
| Module Coordinator/s | Prof. Mimi Zhang |
Module Learning Outcomes
On successful completion of this module, students will be able to:
MLO 1 Load and manipulate data for analysis in R.
MLO 2 Implement in R the statistical techniques that are taught in ST8001.
MLO 3 Interpret the output of the statistical techniques that R produces.
Module Content
The module sessions are:
Session 1: Installing and Running R.
Session 2: Data Import and Export in R and Data Visualization with R.
Session 3: Point Estimates and Confidence Intervals with R.
Session 4: Frequency Data and Proportions with R.
Teaching and learning Methods
This module has 4 sessions that are released during the teaching of ST8001. The online tutorial for each session will take place the week after it is released.
Assessment Details
The module is assessed by a individual project (100%)
Reassessment is a take-home exam, 5hrs duration, and the grade will be capped at 50.
Contact Hours and Indicative Student Workload
| Contact Hours (scheduled hours per student over full module), broken down by: | 17 hours |
| Lecture | 5 hours |
| laboratory | hours |
| tutorial | 12 hours |
| Independent study (outside scheduled contact hours), broken down by: | 45 hours |
| preparation for classes and review of material (including preparation for examination, if applicable) | 25 hours |
| completion of assessments (including examination, if applicable) | 20 hours |
| Total Hours | 62 hours |
Recommended Reading List
The core reading material is of course the module study notes.
The R project website has an extensive online manual at https://cran.rproject.org/manuals.html
Davies, “The Book of R: A First Course in Programming and Statistics”, 1st edition. Published by No Starch Press.
James, Witten, Hastie and Tibshirani, “An Introduction to Statistical Learning: with Applications in R”, published by Springer.
Module Pre-requisites
Prerequisite modules: None.
Other/alternative non-module prerequisites: None.
Module Co-requisites