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ETF9121 - Data analysis in business

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

Postgraduate Faculty of Business and Economics

Leader(s): Dr Ann Maharaj

Offered

Caulfield First semester 2009 (Day)
Caulfield Second semester 2009 (Evening)

Synopsis

This unit will introduce statistical concepts and their applications to business sectors of finance, accounting, marketing and management. Topics covered include: sampling techniques, confidence intervals and hypothesis testing (for both single populations and between populations). The multiple regression models and time series models -- that are very popular in data analysis and forecasting in public sectors and industries -- will be covered in detail in this unit. Prerequisites ETX1100 or AFX9510 will not apply to students who enrol in the Graduate Diploma in Applied Econometrics, the Graduate Certificate in Applied Econometrics or the Executive Certificate in Applied Econometrics.

Objectives

The learning goals associated with this unit are to:

  • define different sampling techniques and use Excel to generate samples from these techniques
  • demonstrate an understanding of the role of inference and hypothesis testing in statistics and their value when applied in financial, marketing and management fields
  • conduct hypothesis tests for means and proportions of single populations, identify significant differences between two populations in terms of means, proportions and variances and interpret the value of these techniques in business
  • interpret and analyse the results of a regression analysis using a linear model, a model which incorporates dummy variables, or models involving nonlinear terms
  • interpret and analyse the results of time series analysis (generated using Excel) including methods of classical decomposition and exponential smoothing.

Assessment

Within semester assessment: 40%
Examination (2 hours): 60%

Contact hours

One 2-hour lecture and one 1-hour laboratory/tutorial session per week

Prerequisites

Students must be enrolled in course codes 3814, 3815, 3816 or 3822 or must have passed ETX1100 or AFX9510

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