| Module Code | STP80140 |
| Module Name | Time Series |
| ECTS Weighting[1] | 5 ECTS |
| Semester taught | Semester 2 |
| Module Coordinator/s | Dr Emma Howard |
Module Learning Outcomes
On successful completion of this module, students will be able to:
LO1: Define and describe the different patterns that can be found in times series and propose algorithms and statistical models that are suitable for their analysis.
LO2: Program, analyse and select the best model for forecasting.
LO3: Interpret output of data analysis performed by a computer statistics package.
LO4: Compute predictions with their confidence intervals using the selected model.
Module Content
Specific topics addressed in this module include:
- Basic Forecasting Methods
- Exponential Smoothing Methods and Models
- Assessing Model Fit and Forecasting Accuracy
- ARIMA
- Advanced Forecasting
Teaching and learning Methods
This module is taught over 4 weekly sessions (weeks 5-8 of the TCD Hilary Teaching Term). The module content is taught through online videos. All content is available through Blackboard. Each week will also feature a one hour synchronous online tutorial and a one hour synchronous R software lab. These will be taught by the module lecturer and/or teaching assistant.
Assessment Details
| Assessment Component | Brief Description | Learning Outcomes Addressed | % of Total |
| Continuous Assessment | Individual project | L01-L04 | 80% |
| Continuous Assessment | Session quizzes | L01-L04 | 20% |
Reassessment Details
Take Home Exam 100%
Contact Hours and Indicative Student Workload
| Contact Hours (Video Material): | 8 hours |
| Contact Hours (Online tutorials and software labs): | 8 hours |
| Independent study (outside scheduled contact hours), broken down by: | 100hours |
| Total Hours | 116hours |
All content will be delivered online (mix of synchronous and asynchronous formats).
Recommended Reading List
Hyndman, R.J., & Athanasopoulos, G. (2021) Forecasting: principles and practice, 3rd edition, OTexts: Melbourne, Australia. OTexts.com/fpp3.
Module Pre-requisites
Prerequisite modules:
Other/alternative non-module prerequisites: None.