Credit Points 10

Legacy Code 300700

Coordinator Volker Gebhardt Opens in new window

Description Statistical Decision Making introduces students to various statistical techniques for analysing and interpreting data. Presentation of the content will emphasise the correct principles and procedures for collecting and analysing data, using statistical software. Topics include describing different sets of data, probability distributions, statistical inference, and simple linear regression and correlation. The open-source statistical software package R will be introduced and used in this subject. Analysing and interpreting data is crucial in many sectors of modern economy and society. Thus, basic competencies in statistics, data collection and data analysis are essential employability skills in virtually every profession.

School Computer, Data & Math Sciences

Discipline Statistics

Student Contribution Band HECS Band 1 10cp

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Level Undergraduate Level 1 subject

Equivalent Subjects COMP1014
MATH1033

Incompatible Subjects MATH1003
MATH1025
MATH1032
MATH1030
ECON1006
MATH1012

Learning Outcomes

On successful completion of this subject, students should be able to:

1. Analyse data using traditional methods or modern resampling methods
2. Use technology to assist in performing statistical analysis
3. Recognise the limitations of data collection methods and demonstrate awareness of the influence of these limitations on inference
4. Choose the correct statistical method for analysis and correctly interpret the results
5. Aanalyse data using traditional methods or modern resampling methods
6. Recognise the limitations in data collection methods and have awareness in the role of data collection on inference

Subject Content

Collecting and describing data
Probability
Confidence intervals and hypothesis tests
Simple linear regression