Year
2021
Units
4.5
Contact
1 x 3-hour workshop weekly
Prerequisites
BUSN1009 - Quantitative Methods
Enrolment not permitted
1 of BUSN2001, ECON3006, ECON7028 has been successfully completed
Assumed knowledge
Familiarity with basic Microsoft excel techniques such as can be obtained in BUSN1009 Quantitative Methods.
Topic description

The topic will provide students with the opportunity to develop skills in business forecasting. It will explain how to make business forecasts in circumstances where there is little information available and situations where considerable data are available. Major business data sources are reviewed and methods of processing data to generate good forecasts are described. These methods include regression, time series analysis and judgmental procedures. Students use Microsoft Excel computer software to apply the techniques in business forecasting situations.

Educational aims

This topic aims to provide students with the knowledge to develop the required skills necessary in business forecasting.

Expected learning outcomes
On completion of this topic you will be expected to be able to:

  1. Obtain information and process that information to make good business forecasts in situations where there is much information and where there is little
  2. Use the business software package Excel to carry out statistical tests, multiple regression and time series analysis
  3. Use statistical and judgmental methods to make business and marketing forecasts

Key dates and timetable

(1), (2)

Each class is numbered in brackets.
Where more than one class is offered, students normally attend only one.

Classes are held weekly unless otherwise indicated.

FULL

If you are enrolled for this topic, but all classes for one of the activities (eg tutorials) are full,
contact your College Office for assistance. Full classes frequently occur near the start of semester.

Students may still enrol in topics with full classes as more places will be made available as needed.

If this padlock appears next to an activity name (eg Lecture), then class registration is closed for this activity.

Class registration normally closes at the end of week 2 of each semester.

Classes in a stream are grouped so that the same students attend all classes in that stream.
Registration in the stream will result in registration in all classes.
  Unless otherwise advised, classes are not held during semester breaks or on public holidays.