Week 1: What is forecasting?
What you will learn this week
- How to think about forecasting from a statistical perspective
- What makes something easy or hard to forecast?
- Using the
tsibblepackage in R
Tutorial exercises
The main tasks for Week 1 tutorials will be:
- To ensure that you have successfully installed R and RStudio on your own laptop.
- Walk through IA_template. Make sure you understand the quarto (qmd) file structure and make sure you can knit the file successfully to pdf format.
- Work your way through Getting started (5 modules) and Writing documents (1 module) in startR. This is material we have prepared for you and other Monash students working in R. You should do these at your own pace to understand the concepts.
- Discuss IA1 in class. How do you go about forecasting at the moment that you are untrained?
Your tutors will be in your tutorial class to assist you.
Pre-class activities
Before we start classes, make sure you are familiar with R, RStudio and the tidyverse packages. If you’ve already done one of ETX2250/ETC1010 or something equivalent you should be fairly familiar with these concepts and probably will not need much help. If you’re new to R and the tidyverse, then you will need to get yourself up-to-speed.
- Install/update R, RStudio. See https://otexts.com/fpp3/appendix-using-r.html
- Install required packages
install.packages(c("tidyverse","fpp3", "GGally"), dependencies = TRUE) - Explore StartR: https://startr.numbat.space/. Work through Getting started (5 modules) and Writing documents (1 module). Do as much of it as you think you need. For those students new to R, it is strongly recommended that you do all these. For those who have previously used R, concentrate on the parts where you feel you are weakest.
- Read Chapter 1 of the textbook and watch all embedded videos. Pay particular attention to Section 1.7.
- Read Section 2.1 of the textbook and watch the embedded video.
Slides for seminar
Workshop activities
In-class Code
Assignments
- IA1 is due on Monday 10 March.