Fundamentals of Demand Forecasting

Course Summary

15

print this page

Course Outline

This course introduces the idea of forecasting using causal and time series methods to estimate demand for a product or service. Examples are drawn from passenger and freight transport. Students must have a basic understanding of statistics and have some proficiency with Excel.

Course Objectives:

  1. Introduction to forecasting
  2. Expert opinion, Delphi, judgement
  3. Time series – patterns in data
  4. Moving averages and exponential smoothing
  5. Brown’s model for forecasting cyclical demand
  6. Causal or econometric modelling
  7. Data problems – multicollinearity, autocorrelation, heteroscedasticity
  8. Using Excel for demand forecasting
  9. Q – an introduction

Learning Outcomes

On completion students will be able to develop simple econometric and time series of models to forecast demand for a product or service using Excel or a statistical package – SPSS or Q.

Duration

2 Days in Melbourne

Delivery Mode

Classroom

Pre-Requisites

This course assumes knowledge of elementary statistics such as “Statistics for Logistics” or an equivalent subject at least at high school statistics level. It is also assumed students can use a spreadsheet such as Microsoft Excel.

Fees

On Application

Commencement Dates

On Application

Location:


Course Contact:

Dr. David Wilson
http://masterresearch.com.au
+61 419 374 776