Biostatistics
Unit of study table
Master of Biostatistics |
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|---|---|---|
| Students must complete 72 credit points, including: | ||
| (a) 6 credit points from Epidemiology units of study; and | ||
| (b) 30 credits points from Biostatistics Part 1 units of study; and | ||
| (c) a minimum of 18 credit points from Biostatistics Part 2 units of study; and | ||
| (d) a maximum of 12 credit points from General Elective units of study; and | ||
| (e) a minimum of 6 credit points of Capstone units of study. | ||
Graduate Diploma in Biostatistics |
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| Students must complete 48 credit points, including: | ||
| (a) 6 credit points from Epidemiology units of study; and | ||
| (b) 30 credit points from Biostatistics Part 1 units of study; and | ||
| (c) a minimum of 6 credit points from Biostatistics Part 2 units of study; and | ||
| (d) a maximum of 6 credit points from General Elective units of study. | ||
Graduate Certificate in Biostatistics |
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| Students must complete 24 credit points, including: | ||
| (a) 6 credit points from Epidemiology units of study; and | ||
| (b) 18 credit points from Biostatistics Part 1 or Biostatistics Part 2 units of study. |
| Unit of study | Credit points | A: Assumed knowledge P: Prerequisites C: Corequisites N: Prohibition |
|---|---|---|
Epidemiology |
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| All students must complete 6 credit points from Epidemiology. | ||
| CEPI5100 Introduction to Clinical Epidemiology |
6 | |
| PUBH5010 Epidemiology Methods and Uses |
6 | N BSTA5011 |
Biostatistics Part 1 |
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| Graduate Diploma and Master students must complete 30 credit points from Biostatistics Part 1. | ||
| BSTA5002 Principles of Statistical Inference (PSI) |
6 | P BSTA5100 or (BSTA5001 and BSTA5023) |
| BSTA5004 Data Management and Stats Computing (DMC) |
6 | |
| BSTA5100 Mathematics Foundations of Biostatistics (MFB) |
6 | N BSTA5023 |
| BSTA5210 Regression Modelling for Biostatistics 1 (RM1) |
6 | P (BSTA5011 or PUBH5010 or CEPI5100) C BSTA5002 N BSTA5007 or BSTA5008 |
| BSTA5211 Regression Modelling for Biostatistics 2 (RM2) |
6 | P (BSTA5210 or BSTA5007) N BSTA5008 and BSTA5009 |
Biostatistics Part 2 |
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| Graduate Diploma students must complete a minimum of 6 credit points from Biostatistics Part 2. Masters students must complete a minimum of 18 credit points from Biostatistics Part 2. | ||
| BSTA5003 Health Indicators and Health Surveys (HIS) |
6 | C BSTA5100 or BSTA5001 |
| BSTA5005 Clinical Biostatistics (CLB) |
6 | P (PUBH5010 or BSTA5011 or CEPI5100) and BSTA5002 C BSTA5210 or BSTA5007 |
| BSTA5006 Design of Randomised Controlled Trials (DES) |
6 | P (PUBH5010 or BSTA5011 or CEPI5100) and (BSTA5100 or BSTA5023) C BSTA5002 |
| BSTA5012 Longitudinal and Correlated Data (LCD) |
6 | P BSTA5210 or BSTA5211 or (BSTA5007 and BSTA5008) |
| BSTA5013 Statistical Genomics (SGX) |
6 | P BSTA5004 and (BSTA5210 or BSTA5211 or BSTA5007) |
| BSTA5014 Bayesian Statistical Methods (BAY) |
6 | P BSTA5210 or BSTA5211 or (BSTA5007 and BSTA5008) |
| BSTA5017 Causal Inference (CSI) |
6 | P BSTA5210 or BSTA5211 or (BSTA5007 and BSTA5008) |
| BSTA5018 Machine Learning for Biostatistics (MLB) |
6 | P (PUBH5010 or BSTA5011 or CEPI5100) and (BSTA5007 or BSTA5210 or BSTA5211 or PUBH5217) |
| PUBH5215 Analysis of Linked Health Data |
6 | A The unit assumes introductory-level programming skills in SAS or R, assumes introductory-level knowledge in epidemiology, e.g., PUBH5010 or CEPI5100, and introductory-level knowledge in biostatistics or statistics, e.g., PUBH5018 or FMHU5002. C (PUBH5010 or BSTA5011 or CEPI5100) and (PUBH5211 or PUBH5217 or BSTA5004) |
General Electives |
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Graduate Diploma students can complete a maximum of 6 credit points from General Electives. Master students can complete a maximum of 12 credit points from General Electives. Students are encouraged to contact the Program Coordinator prior to enrolling into these units. |
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Analytic Methods |
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| CEPI5105 Advanced Epidemiology |
6 | P (CEPI5100 or PUBH5010) and (FMHU5002 or PUBH5018 or BSTA5002) C PUBH5217 or BSTA5210 |
| CEPI5215 Writing and Reviewing Medical Papers |
6 | A Some basic knowledge of summary statistic is assumed P (PUBH5010 or CEPI5100 or BSTA5011) N CEPI5214 |
| HPOL5000 Health Policy and Health Economics |
6 | N PUBH5032 |
| PUBH5125 Environmental and Social Epidemiology |
6 | C PUBH5010 or CEPI5100 or BSTA5011 P PUBH5010 or CEPI5100 or BSTA5011 |
| PUBH5224 Applied Epidemiology |
6 | P (PUBH5010 or CEPI5100 or BSTA5011) and (PUBH5018 or FMHU5002 or BSTA5002) |
| PUBH5300 Infectious Disease Epidemiology |
6 | A A basic understanding of introductory statistics and generalised linear regression (as would be attained through a unit such as PUBH5217 or equivalent, or through equivalent experience). No previous coding experience is required or assumed |
| PUBH5312 Health Economic Evaluation |
6 | P HPOL5000 or FMHU5001 or BSTA5002 N PUBH5302 |
| FMHU5003 Introduction to Qualitative Research in Health |
6 | N PUBH5505 or BACH5255 or QUAL5005 |
| FMHU5004 Qualitative Analysis and Writing in Health |
6 | A Students should have an understanding of qualitative research as this unit does not cover research design or data collection. Students looking for an introductory level unit should take FMHU5003 Introduction to Qualitative Research in Health. P FMHU5003 or PUBH5505 or QUAL5005 or QUAL5006 or GLOH5201 N PUBH5506 |
| PUBH5317 Advanced Economic and Decision Analysis |
6 | P (PUBH5010 or CEPI5100 or BSTA5011) and (PUBH5018 or FMHU5002 or BSTA5002) C PUBH5312 N PUBH5205 or PUBH5307 |
Data Science |
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| COMP5048 Visual Analytics |
6 | A Experience with data structures and algorithms as covered in COMP9103 or COMP9003 or COMP2123 or COMP2823 or INFO1105 or INFO1905 (or equivalent UoS from different institutions) |
| COMP5310 Principles of Data Science |
6 | A Good understanding of relational data model and database technologies as covered in ISYS2120 or COMP9120 (or equivalent UoS from different institutions) N INFO3406 or OCMP5310 |
| COMP5329 Deep Learning |
6 | |
| COMP5338 Advanced Data Models |
6 | A This unit of study assumes foundational knowledge of relational database systems as taught in COMP5138/COMP9120 (Database Management Systems) or INFO2120/INFO2820/ISYS2120 (Database Systems 1) |
| COMP9120 Database Management Systems |
6 | A Some exposure to programming and some familiarity with data model concepts N INFO2120 or INFO2820 or INFO2005 or INFO2905 or COMP5138 or ISYS2120 Students who have previously studied an introductory database subject as part of their undergraduate degree should not enrol in this foundational unit as it covers the same foundational content |
| HTIN5005 Applied Healthcare Data Science |
6 | N HTIN4005 |
Ethics |
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| BETH5202 Research Ethics |
6 | A A three-year undergraduate degree in science, medicine, nursing, allied health sciences, philosophy/ethics, sociology/anthropology, law, history, or other relevant field, or by special permission N BETH5208 |
| BETH5203 Public Health Ethics |
6 | N BETH5206 |
| BETH5204 Clinical Ethics |
6 | |
| BETH5208 Introduction to Human Research Ethics |
2 | N BETH5202 |
| BETH5209 Medicines Policy, Economics and Ethics |
6 | A A degree in science, medicine, pharmacy, nursing, allied health, philosophy/ethics, sociology/anthropology, history, law, communications, public policy, business, economics, commerce, organisation studies, or other relevant field, or by special permission |
Capstone |
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| Master students must complete a minimum of 6 credit points from Capstone. | ||
| BSTA5020 Biostatistics Research Project 1 |
6 | P 48 credit points including BSTA5004 and (BSTA5008 or BSTA5009 or BSTA5210 or BSTA5211) |
| BSTA5021 Biostatistics Research Project 2 |
6 | P 48 credit points including BSTA5004 and (BSTA5008 or BSTA5009 or BSTA5210 or BSTA5211) C BSTA5020 |
| BSTA5030 Professional Practice in Biostatistics |
6 | P 60 credit points including PUBH5215 and BSTA5211 N BSTA5020 or BSTA5021 |
