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

Check your fees via the Fees page.

Level Undergraduate Level 1 subject

Equivalent Subjects MATH 1003
COMP 1014
MATH 1033

Incompatible Subjects MATH 1025
MATH 1032
MATH 1030
ECON 1006
MATH 1012

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

Subject Content

1. Collecting and describing data
2. Probability
3. Confidence intervals and hypothesis tests
4. Simple linear regression