Centre for Applied Statistics

Forecasting: Principles and Practice - September 2017

Further information

Short courses

Duration

3 days


Dates and Time

  • 26-28 September 2017

Course will run from 9am - 5pm all days. Registration will open at 8.45am on the first day.


Facilitator


Venue

The University Club

Terms and conditions

Short Course terms and conditions

Contact us

 

Forecasting is required in many situations: deciding whether to build another power generation planting the next five years requires forecasts of future demand; scheduling staff in a call centre next week requires forecasts of call volume; stocking an inventory requires forecasts of stock requirements. Forecasts can be required several years in advance (for the case of capital investments), or only a few minutes beforehand (for telecommunication routing). Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning.

 

Short-Course Description

 

In this course, we will explore methods and models for forecasting time series. Topics to be covered include seasonality and trends, exponential smoothing, ARIMA modelling, dynamic regression and state space models, as well as forecast accuracy methods and forecast evaluation techniques such as cross-validation.

Course participants will be assumed to be familiar with basic statistical tools such as multiple regression, but no knowledge of time series or forecasting will be assumed. Some prior experience in R is highly desirable.

 

Outline

  • Day 1: Forecasting tools, time series graphics, seasonality and trends, exponential smoothing
  • Day 2: State space models, stationarity, transformations, differencing, ARIMA models.
  • Day 3: Time series cross-validation, dynamic regression, hierarchical forecasting, nonlinear models.


The short-course will involve a mixture of lectures and practical sessions using R. Each participant must bring his or her own laptop with R installed. One week before the course we will send you instructions on how to install R and any associated packages required for the course.

Costs

  • $880 for UWA postgraduate research students/SSAI student members (Early bird $750)
  • $1650 for UWA Staff members/SSAI members (Early bird $1400)
  • $2200 for all others (Early bird $1870)

Early bird discount finishes 13 August 2017. All prices are inclusive of GST.


Enrolment

 
 

Centre for Applied Statistics

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Last updated:
Thursday, 16 February, 2017 12:04 PM

http://www.cas.maths.uwa.edu.au/2559082