ETC3550/5550 Applied forecasting

Teaching team

Maliny Po

Nuwani Palihawadana

Xiefei (Sapphire) Li

Week	Topic	Chapter	Assignments	Quizzes
03 Mar	Introduction to forecasting and R	1. Getting started	Forecasting Competition
10 Mar	Time series graphics	2. Time series graphics		Week 2
17 Mar	Time series decomposition	3. Time series decomposition		Week 3
24 Mar	Simple forecasting methods	5. The forecaster’s toolbox	Assignment 1	Week 4
31 Mar	Accuracy evaluation	5. The forecaster’s toolbox		Week 5
07 Apr	Exponential smoothing	8. Exponential smoothing		Week 6
14 Apr	Exponential smoothing	8. Exponential smoothing	Assignment 2	Week 7
21 Apr	Mid-semester break
28 Apr	ARIMA models	9. ARIMA models		Week 8
05 May	ARIMA models	9. ARIMA models		Week 9
12 May	ARIMA models	9. ARIMA models	Assignment 3	Week 10
19 May	Multiple regression and forecasting	7. Time series regression models		Week 11
26 May	Dynamic regression	10. Dynamic regression models	Retail Project

Here is the code to install the R packages we will be using in this unit.

install.packages(c("tidyverse","fpp3", "GGally"), dependencies = TRUE)