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

Check your HECS Band contribution amount via the Fees page.

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

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

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.

View timetable Opens in new window