units

ETX9000

Faculty of Business and Economics

18 September 2017 22 November 2024
Monash University

Postgraduate - 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.

LevelPostgraduate
FacultyFaculty of Business and Economics
OfferedCaulfield First semester 2012 (Day)
Caulfield First semester 2012 (Evening)
Caulfield Second semester 2012 (Day)
Coordinator(s)Dr Jill Wright, Dr Phillip Edwards

Synopsis

An introduction to descriptive statistics - the collection, organisation, presentation and analysis of grouped and ungrouped data using measures of location and dispersion; the construction of index numbers, with application to share price indices and the CPI; analysis of relationships between variables using simple multiple regression, with applications to forecasting; main ideas of probability theory as a foundation for statistical inference; concept of sampling as a way of capturing uncertainty about data; estimators and their properties; constructing and interpreting confidence intervals, testing a hypothesis, including analysis of variance. Applications to economic data will be emphasised.

Outcomes

The learning goals associated with this unit are to:

  1. interpret business and economic data using descriptive statistics techniques for grouped and ungrouped data, including graphical presentations and measures of location and dispersion
  2. construct and interpret index numbers with application to share price indices and deflation using the Consumer Price Index
  3. describe the concept of a sampling distribution, estimators and their properties as a foundation for statistical inference, and use p-values to make inference on single population means for business and economic decision-making
  4. interpret and evaluate relationships between variables for business and economic decision-making using simple linear regression, including inference, confidence intervals and prediction
  5. apply the main ideas of probability theory, discrete and continuous probability distributions to account for uncertainty in data used for business and economic decision-making.
  6. develop the skills for critical analysis of statistical reporting and inference.

Assessment

Within semester assessment: 50%
Examination (3 hours): 50%

Chief examiner(s)

Dr Jill Wright

Contact hours

3 hours per week

Prohibitions

AFX9510, ETC1000, ETG1102, ETW1000, ETW1102, ETX1100 and ETC9000.