units

ETX1100

Faculty of Business and Economics

Undergraduate - Unit

This unit entry is for students who completed this unit in 2012 only. For students planning to study the unit, please refer to the unit indexes in the the current edition of the Handbook. If you have any queries contact the managing faculty for your course or area of study.

print version

6 points, SCA Band 0 (NATIONAL PRIORITY), 0.125 EFTSL

Refer to the specific census and withdrawal dates for the semester(s) in which this unit is offered, or view unit timetables.

LevelUndergraduate
FacultyFaculty of Business and Economics
OfferedBerwick First semester 2012 (Day)
Caulfield First semester 2012 (Day)
Caulfield First semester 2012 (Evening)
Caulfield Second semester 2012 (Day)
Coordinator(s)Dr Jill Wright (Berwick); Dr Phillip Edwards (Caulfield)

Synopsis

Students will learn to use basic statistical techniques and apply them to problems in accounting, finance, management, marketing and business in general. Students should also be able to effectively communicate the results of their analyses. This unit covers descriptive statistics for revealing the information contained in data; probability as a tool for dealing with uncertainty; probability distributions to model business behaviour; confidence interval estimation and hypothesis testing techniques for single populations; analysis of relationships between variables using simple linear regression; and simple tools for forecasting time series data. Excel software will be used.

Outcomes

The learning goals associated with this unit are to:

  1. interpret business data using descriptive statistics techniques, including the use of Excel spreadsheet functions
  2. apply simple concepts of probability and probability distributions to problems in business decision-making
  3. describe the role of statistical inference and apply inference methods to single populations
  4. interpret and evaluate relationships between variables for business decision-making, using the concept of correlation and simple linear regression
  5. apply suitable statistical techniques for describing and forecasting time series data.

Assessment

Within semester assessment: 30%
Examination (2 hours): 70%

Chief examiner(s)

Dr Jill Wright

Contact hours

3 hours per week

Prerequisites

It is highly recommended that students have done Year 12 Mathematics (any).

Prohibitions

BMS11,BUS1100, ETC1000, ETG1102, ETW1000, ETW1102, PMM2020, SCI1020