MATH 1028 Statistical Decision Making
Credit Points 10
Legacy Code 300700
Coordinator Volker Gebhardt Opens in new window
Description Statistical Decision Making introduces students to various statistical techniques supporting the study of computing and science. Presentation of the content will emphasize the correct principles and procedures for collecting and analysing scientific data, using information and communication technologies. Topics include describing different sets of data, probability distributions, statistical inference, and simple linear regression and correlation.
School Computer, Data & Math Sciences
Student Contribution Band HECS Band 1 10cp
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Level Undergraduate Level 1 subject
Equivalent Subjects MATH 1032 Statistics for Science MATH 1003 Biometry MATH 1030 Statistics for Business ECON 1006 Introduction to Economic Methods MATH 1012 Management Analytics MATH 1031 Statistics for Business (WSTC) MATH 1004 Biometry (WSTC) MATH 1029 Statistical Decision Making (WSTC)
Incompatible Subjects MATH 1025 Quantitative Techniques
Learning Outcomes
- Analyse data using traditional methods or modern resampling methods
- Use technology to assist in performing statistical analysis
- Recognise the limitations of data collection methods and demonstrate awareness of the influence of these limitations on inference
- Choose the correct statistical method for analysis and correctly interpret the results
- Aanalyse data using traditional methods or modern resampling methods
- Recognise the limitations in data collection methods and have awareness in the role of data collection on inference
Subject Content
Probability
Confidence intervals and hypothesis tests
Simple linear regression
Assessment
The following table summarises the standard assessment tasks for this subject. Please note this is a guide only. Assessment tasks are regularly updated, where there is a difference your Learning Guide takes precedence.
| Item | Length | Percent | Threshold | Individual/Group Task |
|---|---|---|---|---|
| Short Answer Test | 50 minutes | 11 | Y | Individual |
| Short Workshop Exercises | 15 minutes each | 24 | N | Individual |
| Team Project | 15 hours each | 15 | N | Individual |
| Final Exam | 2 hours | 50 | Y | Individual |
Prescribed Texts
- Lock, R. H., Lock, P. F., Morgan, K. L., Lock, E. F., & Lock, D. F. (Eds.). (2013). Statistics : unlocking the power of data. Hoboken, N.J.: Wiley.
Teaching Periods
2022 Semester 1
Campbelltown
Day
Subject Contact Volker Gebhardt Opens in new window
Attendance Requirements 80% attendance rate is imposed in all core subjects’ due to the nature of class activities that are aligned with subject assessments.
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Penrith (Kingswood)
Day
Subject Contact Volker Gebhardt Opens in new window
Attendance Requirements 80% attendance rate is imposed in all core subjects’ due to the nature of class activities that are aligned with subject assessments.
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Parramatta - Victoria Rd
Day
Subject Contact Volker Gebhardt Opens in new window
Attendance Requirements 80% attendance rate is imposed in all core subjects’ due to the nature of class activities that are aligned with subject assessments.
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2022 Trimester 1
Sydney City
Day
Subject Contact Antoinette Cevenini Opens in new window
Attendance Requirements 80% attendance rate is imposed in all core subjects’ due to the nature of class activities that are aligned with subject assessments.
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2022 Trimester 3
Sydney City
Day
Subject Contact Antoinette Cevenini Opens in new window
Attendance Requirements 80% attendance rate is imposed in all core subjects’ due to the nature of class activities that are aligned with subject assessments.