units

ETX9000

Faculty of Business and Economics

Skip to content | Change text size
 

print version

Monash University Handbook 2010 Postgraduate - Unit

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

LevelPostgraduate
FacultyFaculty of Business and Economics
OfferedCaulfield First semester 2010 (Day)
Caulfield First semester 2010 (Evening)
Clayton First semester 2010 (Day)
Clayton Second semester 2010 (Day)
Australia (Other) First semester 2010 (Off-campus block of classes)
Australia (Other) Second semester 2010 (Off-campus block of classes)
Coordinator(s)Dr Phillip Edwards, Dr Neil Diamond

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.

Objectives

The learning goals associated with this unit are to:

  • interpret business and economic data using descriptive statistics techniques for grouped and ungrouped data, including graphical presentations and measures of location and dispersion
  • construct and interpret index numbers with application to share price indices and deflation using the Consumer Price Index
  • 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
  • interpret and evaluate relationships between variables for business and economic decision-making using simple linear regression, including inference, confidence intervals and prediction
  • 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.
  • develop the skills for critical analysis of statistical reporting and inference.

Assessment

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

Chief examiner(s)

Kathryn Cornwell

Contact hours

One 2 hour lecture and one 1 hour tutorial per week

Prohibitions

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