Session 1

summary: You will learn about the forecasting process and how to identify what to forecast for a given decision. Moreover, you analyse key features of a time series and use time series graphics in R to detect systematic patterns in your data.

Questions

Introduction to forecasting

1. What is the link between forecasting and decision making?
2. What is the forecasting process?
3. What are the main steps in a forecasting task?
4. How to identify what to forecast?
5. What are factors affecting forecastability?
6. How to present forecasts?

Time series patterns and graphic

1. What are the key features of a time series?
2. How to detect systematic patterns in the time series?
3. which tome series graphics should we use to better understand patterns?
4. what is the characteristics of a white noise series?

Schedule

Readings