ETF3231/5231 Business Forecasting
Lecturer/Chief Examiner
Weekly schedule
Pre-class preparation, pre-recorded videos, approximately 1 hour per week.
Seminars, 3pm-4pm Wednesday, Building K Level 3, K321, CA_K_K321.
Workshops, 4pm-5pm Wednesday, Building K Level 3, K321, CA_K_K321.
Tutorials, 50 minutes in class per week.
Lecture Recordings: TBA, coming soon 🚒.
| Week | Topic | Chapter | Assignment | Quiz |
|---|---|---|---|---|
| 02 Mar | Introduction to forecasting and R | 1. Getting started | ||
| 09 Mar | Time series graphics | 2. Time series graphics | IA1 | Week 2 |
| 16 Mar | Time series decomposition | 3. Time series decomposition | Week 3 | |
| 23 Mar | The forecaster’s toolbox | 5. The forecaster’s toolbox | GA1 | Week 4 |
| 30 Mar | Exponential smoothing | 8. Exponential smoothing | IA2 | Week 5 |
| 06 Apr | Mid-semester break | |||
| 13 Apr | Exponential smoothing | 8. Exponential smoothing | GA2 | |
| 20 Apr | ARIMA models | 9. ARIMA models | IA3 | Week 7 |
| 27 Apr | ARIMA models | 9. ARIMA models | Week 8 | |
| 04 May | ARIMA models | 9. ARIMA models | GA3 | Week 9 |
| 11 May | Multiple regression and forecasting | 7. Time series regression models | IA4 | Week 10 |
| 18 May | Dynamic regression | 10. Dynamic regression models | Week 11 | |
| 25 May | Revision | Revision | GA4 | Week 12 |
Assessments
Final exam 60%, in-semester assessment 40% (quizzes and assignments)
Quizzes: There will be weekly quizzes (11 in total), to be completed during the Workshops. These quizzes will cover course content from the corresponding Seminar each week. Hence, attending both Seminars and Workshops is important! You are required to complete 8 out of the 11 quizzes to receive full marks (worth 8% in total). An additional bonus of up to 3% will be awarded, with 1% for each extra quiz completed beyond the required eight. This bonus will contribute towards your final exam mark.
IA: denotes an individual assignment to be completed by all students.
GA: denotes a group assignment to be completed only by ETF5231 students
The due dates will be confirmed throughout the semester as our speed in covering topics will vary depending on student needs.
AI and Generative AI tools can be used selectively to edit your work, improve spelling, grammar, and language. It can help to structure your responses to ensure clarity in explanations. A full declaration of AI use must be provided as per the instructions in the assessment task.
| Weeks | Assessment Task | Weight |
|---|---|---|
| Weekly | Quizzes | 8% |
| 2 | IA1 | 2% |
| 4 | GA1 | 2% |
| 5 | IA2 | 5% |
| 6 | GA2 | 5% |
| 8 | IA3 | 10% |
| 9 | GA3 | 10% |
| 11 | IA4 | 15% |
| 12 | GA4 | 15% |
ETF5231 students: marks allocated to Assignments will be a combination between Individual Assignments and Group Assignments with weights 0.7 and 0.3. So if you score 8/10 for IA3 and 5/10 for GA3 your mark for Assignment 3 will be 8*0.7+5*0.3=7.1 out of 10. Hence, it is important to make sure that groups are performing at the highest standard.
Presentation requirements: using Quarto, and should converted the assignment into pdf output file unless otherwise specified.
Criteria for marking: Provided the task has been completed and your code runs without errors, full marks will be awarded. Marks will be deducted for incomplete tasks or if there are errors.
Penalties for late lodgement: The University has a standard penalty for late submission. See the Marking and Feedback Procedure for more information.
Additional information: Additional information regarding these assessments will be provided during the scheduled class time and on Moodle.
Group participation rules for group assignments (GAs): It is expected that all group members participate equally to the group assignments. It sometimes helps to keep a log of the tasks each member is to complete. This may assist in keeping some balance throughout the semester. To ensure that all group members are contributing the following rules will apply for all the group assignments throughout the semester.
Every group member has the right to express concern/dislike in terms of a group member being absent from group activities. This has to be expressed directly to me (and only me) via a formal email stating facts that have hindered the operations of the group (saying I do not like George because he is tall is not a reason for expressing concern). If at least two such complaints are submitted during the completion of an assignment, the group member concerned will receive a warning. If the situation is not improved during the next assignment and another two complaints are again submitted, the group member will be immediately removed from the group and will be expected to complete the rest of the group assignments alone.
R package installation
Here is the code to install the R packages we will be using in this unit.
install.packages(c("tidyverse","fpp3", "GGally"), dependencies = TRUE)