Postgraduate - UnitETX5900 - Business and economic statistics

This unit entry is for students who completed this unit in 2014 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.

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6 points, SCA Band 2, 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.

Level	Postgraduate
Faculty	Faculty of Business and Economics
Organisational Unit	Department of Econometrics and Business Statistics
Offered	Caulfield First semester 2014 (Day) Clayton First semester 2014 (Day) Caulfield Second semester 2014 (Day) Clayton Second semester 2014 (Day)
Coordinator(s)	Ms Gerrie Roberts

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. Applications to critical analysis of business and economic data will be emphasized. Excel software will be used.

Outcomes

The learning goals associated with this unit are to:

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

Assessment

Within semester assessment: 30%
Examination: 70%

Chief examiner(s)

Ms Gerrie Roberts

Workload requirements

Minimum total expected workload equals 144 hours per semester

Prohibitions

AFX9510, BFF5951, ETC1000, ETG1102, ETP1100, ETW1000, ETW1102, ETX1100, ETX9000, ETC9020, ETC9000.