# Table 1: Computational science

Table 1 lists units of study available to students in the Bachelor of Science and combined degrees. The units are available to students enrolled in other degrees in accordance with their degree resolutions.

Unit of study |
Credit points |
A: Assumed knowledge P: Prerequisites C: Corequisites N: Prohibition |
Session |
---|---|---|---|

## Computational Science |
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For a major in Computational Science the minimum requirement is 24 credit points chosen from the core or elective senior units of study listed for this subject area, of which at least 12 credit points must be core senior units of study. | |||

## Junior units of study |
|||

COSC1003Introduction to Computational Science |
6 | A HSC Mathematics, Linear Algebra N COSC1903 |
Semester 2 |

COSC1903Introduction to Computational Sci (Adv) |
6 | A HSC Mathematics, Linear Algebra P ATAR of at least 90 or at least a distinction in INFO1003 or INFO1903. N COSC1003 |
Semester 2 |

## Senior core units of study |
|||

COSC3011Scientific Computing |
6 | A Programming experience in MATLAB. P 12 credit points chosen from Junior Mathematics and Statistics, 12 credit points of Intermediate units in Science subject areas. N COSC3911, COSC3001, COSC3901, PHYS3301, PHYS3901 |
Semester 1 |

COSC3911Scientific Computing (Advanced) |
6 | A Programming experience in MATLAB. P 12 credit points chosen from Junior Mathematics and Statistics, 12 credit points of Intermediate units in Science subject areas with a credit average. N COSC3011, COSC3001, COSC3901, PHYS3301, PHYS3901 |
Semester 1 |

MATH3076Mathematical Computing |
6 | P 12 credit points of Intermediate Mathematics and one of (MATH1001 or MATH1003 or MATH1901 or MATH1903 or MATH1906 or MATH1907) N MATH3976, MATH3016, MATH3916 |
Semester 1 |

MATH3976Mathematical Computing (Advanced) |
6 | P 12 credit points of Intermediate Mathematics and one of (MATH1903 or MATH1907) or Credit in MATH1003 N MATH3076, MATH3016, MATH3916 |
Semester 1 |

## Senior elective units of study |
|||

BINF3101Bioinformatics Project |
6 | A INFO2110 and (INFO1103 or INFO1903) P 12 credit points from Intermediate Biology, Molecular Biology and Genetics, Biochemistry, Microbiology, Pharmacology N COMP3206, BINF3001, INFO3600, SOFT3300, SOFT3600, SOFT3200, SOFT3700 |
Semester 2 |

BIOL3006Ecological Methods |
6 | A (BIOL2011 or BIOL2911 or BIOL2012 or BIOL2912) or (PLNT2002 or PLNT2902) P 12 credit points of Intermediate Biology; or 6 credit points of Intermediate BIOL and one of (ENVI2111 or ENVI2911) or (GEOS2115 or GEOS2915) N BIOL3906 |
Semester 1 |

BIOL3906Ecological Methods (Advanced) |
6 | A BIOL2011 or BIOL2911 or BIOL2012 or BIOL2912 or PLNT2002 or PLNT2902 P Distinction average in 12 credit points of Intermediate Biology; or 6 credit points of Intermediate Biology and (ENVI2111 or ENVI2911) or (GEOS2115 or GEOS2915). These requirements may be varied and students with lower averages should consult the Unit Executive Officer. N BIOL3006 |
Semester 1 |

COMP3308Introduction to Artificial Intelligence |
6 | A COMP2007,programing skills (e.g. Java, Python, C, C++, Matlab) N COMP3608 |
Semester 1 |

COMP3608Intro. to Artificial Intelligence (Adv) |
6 | A Programming skills (e.g. Java, Python, C, C++, Matlab) are required to complete the assignment. P Distinction-level results in some 2nd year COMP or MATH or SOFT units. N COMP3308 |
Semester 1 |

COMP3456Computational Methods for Life Sciences |
6 | P (INFO1105 or INFO1905) and (COMP2007 or INFO2120) and 6 credit points from BIOL or MBLG |
Semester 2 |

MATH3063Differential Equations and Biomaths |
6 | A MATH2061 P 12 credit points of Intermediate Mathematics N MATH3020, MATH3920, MATH3003, MATH3923, MATH3963 |
Semester 1 |

MATH3963Differential Equations & Biomaths (Adv) |
6 | A MATH2961 P 12 credit points of Intermediate Mathematics with average grade of at least credit N MATH3020, MATH3920, MATH3003, MATH3923, MATH3063 |
Semester 1 |

MATH3078PDEs and Waves |
6 | A (MATH2061 or MATH2961) and (MATH2065 or MATH2965) P 12 credit points of Intermediate Mathematics N MATH3978, MATH3018, MATH3921 |
Semester 2 |

MATH3978PDEs and Waves (Advanced) |
6 | A (MATH2061 or MATH2961) and (MATH2065 or MATH2965) P 12 credit points of Intermediate Mathematics with at least Credit average N MATH3078, MATH3018, MATH3921 |
Semester 2 |

STAT3011Stochastic Processes and Time Series |
6 | P (STAT2011 or STAT2911 or STAT2001 or STAT2901) and (MATH1003 or MATH1903 or MATH1907). N STAT3911, STAT3003, STAT3903, STAT3005, STAT3905 |
Semester 1 |

STAT3911Stochastic Processes and Time Series Adv |
6 | P (STAT2911 or credit in STAT2011) and (MATH1003 or MATH1903 or MATH1907) N STAT3011, STAT3003, STAT3903, STAT3005, STAT3905 |
Semester 1 |

STAT3012Applied Linear Models |
6 | P (STAT2012 or STAT2912 or STAT2004) and (MATH1002 or MATH1014 or MATH1902) N STAT3912, STAT3002, STAT3902, STAT3004, STAT3904 |
Semester 1 |

STAT3912Applied Linear Models (Advanced) |
6 | P (STAT2912 or Credit in STAT2004 or Credit in STAT2012) and (MATH2061 or MATH2961 or MATH1902) N STAT3012, STAT3002, STAT3902, STAT3004, STAT3904 |
Semester 1 |

### Computational Science

For a major in Computational Science the minimum requirement is 24 credit points chosen from the core or elective senior units of study listed for this subject area, of which at least 12 credit points must be core senior units of study.

##### Junior units of study

**COSC1003 Introduction to Computational Science**

Credit points: 6 Teacher/Coordinator: Dr Tara Murphy/Dr Pulin Gong Session: Semester 2 Classes: 2 lectures and 3 practicals per week. Prohibitions: COSC1903 Assumed knowledge: HSC Mathematics, Linear Algebra Assessment: One 2-hour final exam, three assignments, and completion of Computation Lab sessions (100%) Associated degrees: B A, B Med Sc, B Sc, B Sc (Molecular Biology & Genetics), UG Study Abroad Program.

This unit of study focuses on scientific problem solving and data visualization using computers. Students will learn how to solve problems arising in the natural sciences and mathematics using core features of MATLAB and C, with a choice of problems from various areas of science. No previous knowledge of programming is assumed.

**COSC1903 Introduction to Computational Sci (Adv)**

Credit points: 6 Teacher/Coordinator: Dr Tara Murphy/Dr Pulin Gong Session: Semester 2 Classes: 2 lectures and 3 practicals per week. Prerequisites: ATAR of at least 90 or at least a distinction in INFO1003 or INFO1903. Prohibitions: COSC1003 Assumed knowledge: HSC Mathematics, Linear Algebra Assessment: One 2-hour final exam, three assignments, and completion of Computation Lab sessions (100%) Associated degrees: B A, B Med Sc, B Sc, B Sc (Molecular Biology & Genetics), UG Study Abroad Program.

This unit of study focuses on scientific problem solving and data visualization using computers. Students will learn how to solve problems arising in the natural sciences and mathematics using core features of MATLAB and C, with a choice of problems from various areas of science. No previous knowledge of programming is assumed.

##### Senior core units of study

**COSC3011 Scientific Computing**

Credit points: 6 Session: Semester 1 Classes: Two 1-hour lectures and one 3-hour practical per week. Prerequisites: 12 credit points chosen from Junior Mathematics and Statistics, 12 credit points of Intermediate units in Science subject areas. Prohibitions: COSC3911, COSC3001, COSC3901, PHYS3301, PHYS3901 Assumed knowledge: Programming experience in MATLAB. Assessment: Assignments, lab, project work and written exam. Associated degrees: B A, B A (Adv)(Hons), B A (Adv)(Hons), M B B S, B E, B Med Sc, B Sc, UG Study Abroad Program.

This unit of study provides a senior-level treatment of scientific problem solving using computers. Students will understand and apply a wide range of numerical schemes for solving ordinary and partial differential equations. Linear algebra is used to provide detailed insight into stability analysis, relaxation methods, and implicit integration. A variety of scientific problems are considered, including planetary motion, population demographics, heat diffusion, traffic flow and quantum mechanics. All coding is performed with MATLAB, and basic programming experience is assumed.

Textbooks

Garcia, AL. Numerical Methods for Physics, 2nd Edition.

**COSC3911 Scientific Computing (Advanced)**

Credit points: 6 Session: Semester 1 Classes: Two 1-hour lectures and one 3-hour practical per week. Prerequisites: 12 credit points chosen from Junior Mathematics and Statistics, 12 credit points of Intermediate units in Science subject areas with a credit average. Prohibitions: COSC3011, COSC3001, COSC3901, PHYS3301, PHYS3901 Assumed knowledge: Programming experience in MATLAB. Assessment: Assignments, lab, project work and written exam. Associated degrees: B A, B A (Adv)(Hons), B A (Adv)(Hons), M B B S, B E, B Med Sc, B Sc, UG Study Abroad Program.

This unit is the Advanced version of COSC3011. The subject matter is very similar, but more challenging problems will be covered.

Textbooks

Garcia, AL. Numerical Methods for Physics, 2nd Edition.

**MATH3076 Mathematical Computing**

Credit points: 6 Session: Semester 1 Classes: Three 1 hour lectures and one 1 hour laboratory per week. Prerequisites: 12 credit points of Intermediate Mathematics and one of (MATH1001 or MATH1003 or MATH1901 or MATH1903 or MATH1906 or MATH1907) Prohibitions: MATH3976, MATH3016, MATH3916 Assessment: One 2 hour exam, assignments, quizzes (100%) Associated degrees: B A, B A (Adv)(Hons), B A (Adv)(Hons), M B B S, B I T (Hons), B Med Sc, B Res Ec, B Sc, B Sc (Molecular Biotechnology), UG Study Abroad Program.

This unit of study provides an introduction to Fortran 95/2003 programming and numerical methods. Topics covered include computer arithmetic and computational errors, systems of linear equations, interpolation and approximation, solution of nonlinear equations, quadrature, initial value problems for ordinary differential equations and boundary value problems.

**MATH3976 Mathematical Computing (Advanced)**

Credit points: 6 Session: Semester 1 Classes: Three 1 hour lectures and one 1 hour tutorial per week. Prerequisites: 12 credit points of Intermediate Mathematics and one of (MATH1903 or MATH1907) or Credit in MATH1003 Prohibitions: MATH3076, MATH3016, MATH3916 Assessment: One 2 hour exam, assignments, quizzes (100%) Associated degrees: B A, B A (Adv)(Hons), B A (Adv)(Hons), M B B S, B I T (Hons), B Med Sc, B Sc, B Sc (Molecular Biotechnology), UG Study Abroad Program.

See entry for MATH3076 Mathematical Computing.

##### Senior elective units of study

**BINF3101 Bioinformatics Project**

Credit points: 6 Teacher/Coordinator: Dr Michael Charleston, Dr Nathan Lo Session: Semester 2 Classes: Meeting with academic supervisor 1hour per week & class meeting 1 hour per week. Prerequisites: 12 credit points from Intermediate Biology, Molecular Biology and Genetics, Biochemistry, Microbiology, Pharmacology Prohibitions: COMP3206, BINF3001, INFO3600, SOFT3300, SOFT3600, SOFT3200, SOFT3700 Assumed knowledge: INFO2110 and (INFO1103 or INFO1903) Assessment: Oral group presentations, individual and group reports (100%) Associated degrees: B Med Sc, B Sc.

This unit will provide students an opportunity to apply the knowledge and practice the skills acquired in the prerequisite and qualifying units, in the context of designing and building a substantial bioinformatics application. Working in groups, students will carry out the full range of activities including requirements capture, analysis and design, coding, testing and documentation.

**BIOL3006 Ecological Methods**

Credit points: 6 Teacher/Coordinator: Assoc Prof Clare McArthur Session: Semester 1 Classes: 2x1 hr lectures/week 1x3 hr practical/week. Prerequisites: 12 credit points of Intermediate Biology; or 6 credit points of Intermediate BIOL and one of (ENVI2111 or ENVI2911) or (GEOS2115 or GEOS2915) Prohibitions: BIOL3906 Assumed knowledge: (BIOL2011 or BIOL2911 or BIOL2012 or BIOL2912) or (PLNT2002 or PLNT2902) Assessment: 1x2 hr exam (40%), practical assignments (including calculations, reports and reviews) (60%) Associated degrees: B A, B A (Adv)(Hons), B A (Adv)(Hons), M B B S, B Env Sys, B Med Sc, B Sc, B Sc (Marine Science), UG Study Abroad Program.

This unit will consider ecology as a quantitative, experimental and theoretical science. It is concerned with the practical skills and philosophical background required to explore questions and test hypotheses in the real world. Application of ecological methods and theory to practical problems will be integrated throughout the unit of study. Lectures will focus on sound philosophical and experimental principles, drawing on real examples for demonstration of concepts, and will be useful as one basis for informed conservation and management of natural populations and habitats. Practical sessions will be used to gain experience in effective sampling,determining patterns of distribution and abundance, estimating ecological variables, and statistically analysing ecological data. Computer simulations and statistical packages for analyses will be used where appropriate.

Textbooks

Dytham, C. 2003. Choosing and using statistics. A biologist's guide. 2nd edition. Blackwell Science. Melbourne.

**BIOL3906 Ecological Methods (Advanced)**

Credit points: 6 Teacher/Coordinator: Assoc Prof C McArthur Session: Semester 1 Classes: 2x1 hr lectures/week, 1x3 hr practical/week. Prerequisites: Distinction average in 12 credit points of Intermediate Biology; or 6 credit points of Intermediate Biology and (ENVI2111 or ENVI2911) or (GEOS2115 or GEOS2915).
These requirements may be varied and students with lower averages should consult the Unit Executive Officer. Prohibitions: BIOL3006 Assumed knowledge: BIOL2011 or BIOL2911 or BIOL2012 or BIOL2912 or PLNT2002 or PLNT2902 Assessment: 1x2 hr exam (40%), practical assignments (including calculations, reports and reviews) (60%). Associated degrees: B A, B A (Adv)(Hons), B A (Adv)(Hons), M B B S, B Med Sc, B Sc, B Sc (Marine Science), UG Study Abroad Program.

This unit has the same objectives as BIOL3006 Ecological Methods, and is suitable for students who wish to pursue certain aspects in greater depth. Entry is restricted, and selection is made from the applicants on the basis of their previous performance. Students taking this unit of study will participate in alternatives to some elements of the standard course and will be required to pursue the objectives by more independent means. Specific details of this unit of study and assessment will be announced in meetings with students in week 1 of semester 1. This unit of study may be taken as part of the BSc (Advanced) program.

Textbooks

As for BIOL3006

**COMP3308 Introduction to Artificial Intelligence**

Credit points: 6 Session: Semester 1 Classes: (Lec 2hrs & Tut 1hr) per week Prohibitions: COMP3608 Assumed knowledge: COMP2007,programing skills (e.g. Java, Python, C, C++, Matlab) Assessment: Assignments (50%), Final Exam (50%) Associated degrees: B A, B A (Adv)(Hons), B A (Adv)(Hons), M B B S, B E, B Med Sc, B Sc, B Sc (Marine Science), B Sc (Molecular Biology & Genetics), UG Study Abroad Program.

Artificial Intelligence (AI) is all about programming computers to perform tasks normally associated with intelligent behaviour. Classical AI programs have played games, proved theorems, discovered patterns in data, planned complex assembly sequences and so on. This unit of study will introduce representations, techniques and architectures used to build intelligent systems. It will explore selected topics such as heuristic search, game playing, machine learning, and knowledge representation. Students who complete it will have an understanding of some of the fundamental methods and algortihms of AI, and an appreciation of how they can be applied to interesting problems. The unit will involve a practical component in which some simple problems are solved using AI techniques.

**COMP3608 Intro. to Artificial Intelligence (Adv)**

Credit points: 6 Session: Semester 1 Classes: (Lec 2hrs & Prac 1hrs) per week. Prerequisites: Distinction-level results in some 2nd year COMP or MATH or SOFT units. Prohibitions: COMP3308 Assumed knowledge: Programming skills (e.g. Java, Python, C, C++, Matlab) are required to complete the assignment. Assessment: Assignments (50%), Final Exam (50%) Associated degrees: B A, B A (Adv)(Hons), B A (Adv)(Hons), M B B S, B E, B Med Sc, B Sc, B Sc (Marine Science), B Sc (Molecular Biology & Genetics), UG Study Abroad Program.

An advanced alternative to COMP3308; covers material at an advanced and challenging level.

**COMP3456 Computational Methods for Life Sciences**

Credit points: 6 Session: Semester 2 Classes: (Lec 2hrs & Prac 2hrs) per week Prerequisites: (INFO1105 or INFO1905) and (COMP2007 or INFO2120) and 6 credit points from BIOL or MBLG Assessment: Assignment (20%), quizzes(10%) and final exam (70%). Associated degrees: B E, B Med Sc, B Sc.

This unit introduces the algorithmic principles driving advances in the life sciences. It discusses biological and algorithmic ideas together, linking issues in computer science and biology and thus is suitable for students in both disciplines. Students will learn algorithm design and analysis techniques to solve practical problems in biology.

**MATH3063 Differential Equations and Biomaths**

Credit points: 6 Session: Semester 1 Classes: Three 1 hour lectures and one 1 hour tutorial per week. Prerequisites: 12 credit points of Intermediate Mathematics Prohibitions: MATH3020, MATH3920, MATH3003, MATH3923, MATH3963 Assumed knowledge: MATH2061 Assessment: One 2 hour exam, assignments, quizzes (100%) Associated degrees: B A, B A (Adv)(Hons), B A (Adv)(Hons), M B B S, B Med Sc, B Res Ec, B Sc, B Sc (Molecular Biotechnology), UG Study Abroad Program.

This unit of study is an introduction to the theory of systems of ordinary differential equations. Such systems model many types of phenomena in engineering, biology and the physical sciences. The emphasis will not be on finding explicit solutions, but instead on the qualitative features of these systems, such as stability, instability and oscillatory behaviour. The aim is to develop a good geometrical intuition into the behaviour of solutions to such systems. Some background in linear algebra, and familiarity with concepts such as limits and continuity, will be assumed. The applications in this unit will be drawn from predator-prey systems, transmission of diseases, chemical reactions, beating of the heart and other equations and systems from mathematical biology.

**MATH3963 Differential Equations & Biomaths (Adv)**

Credit points: 6 Session: Semester 1 Classes: Three 1 hour lectures and one 1 hour tutorial per week. Prerequisites: 12 credit points of Intermediate Mathematics with average grade of at least credit Prohibitions: MATH3020, MATH3920, MATH3003, MATH3923, MATH3063 Assumed knowledge: MATH2961 Assessment: One 2 hour exam, assignments, quizzes (100%) Associated degrees: B A, B A (Adv)(Hons), B A (Adv)(Hons), M B B S, B Med Sc, B Sc, B Sc (Molecular Biotechnology), UG Study Abroad Program.

The theory of ordinary differential equations is a classical topic going back to Newton and Leibniz. It comprises a vast number of ideas and methods of different nature. The theory has many applications and stimulates new developments in almost all areas of mathematics. The applications in this unit will be drawn from predator-prey systems, transmission of diseases, chemical reactions, beating of the heart and other equations and systems from mathematical biology. The emphasis is on qualitative analysis including phase-plane methods, bifurcation theory and the study of limit cycles. The more theoretical part includes existence and uniqueness theorems, stability analysis, linearisation, and hyperbolic critical points, and omega limit sets.

**MATH3078 PDEs and Waves**

Credit points: 6 Session: Semester 2 Classes: Three 1 hour lectures and one 1 hour tutorial per week. Prerequisites: 12 credit points of Intermediate Mathematics Prohibitions: MATH3978, MATH3018, MATH3921 Assumed knowledge: (MATH2061 or MATH2961) and (MATH2065 or MATH2965) Assessment: One 2 hour exam, assignments, quizzes (100%) Associated degrees: B A, B A (Adv)(Hons), B A (Adv)(Hons), M B B S, B Med Sc, B Res Ec, B Sc, B Sc (Molecular Biotechnology), UG Study Abroad Program.

This unit of study introduces Sturm-Liouville eigenvalue problems and their role in finding solutions to boundary value problems. Analytical solutions of linear PDEs are found using separation of variables and integral transform methods. Three of the most important equations of mathematical physics - the wave equation, the diffusion (heat) equation and Laplace's equation - are treated, together with a range of applications. There is particular emphasis on wave phenomena, with an introduction to the theory of sound waves and water waves.

**MATH3978 PDEs and Waves (Advanced)**

Credit points: 6 Session: Semester 2 Classes: Three 1 hour lectures and one 1 hour tutorial per week. Prerequisites: 12 credit points of Intermediate Mathematics with at least Credit average Prohibitions: MATH3078, MATH3018, MATH3921 Assumed knowledge: (MATH2061 or MATH2961) and (MATH2065 or MATH2965) Assessment: One 2 hour exam, assignments, quizzes (100%) Associated degrees: B A, B A (Adv)(Hons), B A (Adv)(Hons), M B B S, B Med Sc, B Sc, B Sc (Molecular Biotechnology), UG Study Abroad Program.

As for MATH3078 PDEs & Waves but with more advanced problem solving and assessment tasks. Some additional topics may be included.

**STAT3011 Stochastic Processes and Time Series**

Credit points: 6 Session: Semester 1 Classes: Three 1 hour lectures and one 1 hour tutorial per week; ten 1 hour computer laboratories per semester. Prerequisites: (STAT2011 or STAT2911 or STAT2001 or STAT2901) and (MATH1003 or MATH1903 or MATH1907). Prohibitions: STAT3911, STAT3003, STAT3903, STAT3005, STAT3905 Assessment: One 2 hour exam, assignments and/or quizzes, and computer practical reports (100%) Associated degrees: B A, B A (Adv)(Hons), B A (Adv)(Hons), M B B S, B Med Sc, B Res Ec, B Sc, UG Study Abroad Program.

Section I of this course will introduce the fundamental concepts of applied stochastic processes and Markov chains used in financial mathematics, mathematical statistics, applied mathematics and physics. Section II of the course establishes some methods of modeling and analysing situations which depend on time. Fitting ARMA models for certain time series are considered from both theoretical and practical points of view. Throughout the course we will use the S-PLUS (or R) statistical packages to give analyses and graphical displays.

**STAT3911 Stochastic Processes and Time Series Adv**

Credit points: 6 Session: Semester 1 Classes: Three 1 hour lecture, one 1 hour tutorial per week, plus an extra 1 hour lecture per week on advanced material in the first half of the semester. Seven 1 hour computer laboratories (on time series) in the second half of the semester (one 1 hour class per week). Prerequisites: (STAT2911 or credit in STAT2011) and (MATH1003 or MATH1903 or MATH1907) Prohibitions: STAT3011, STAT3003, STAT3903, STAT3005, STAT3905 Assessment: One 2 hour exam, assignments and/or quizzes, and computer practical reports (100%) Associated degrees: B A, B A (Adv)(Hons), B A (Adv)(Hons), M B B S, B Med Sc, B Sc, UG Study Abroad Program.

This is an Advanced version of STAT3011. There will be 3 lectures in common with STAT3011. In addition to STAT3011 material, theory on branching processes and birth and death processes will be covered. There will be more advanced tutorial and assessment work associated with this unit.

**STAT3012 Applied Linear Models**

Credit points: 6 Session: Semester 1 Classes: Three 1 hour lectures, one 1 hour tutorial and one 1 hour computer laboratories per week. Prerequisites: (STAT2012 or STAT2912 or STAT2004) and (MATH1002 or MATH1014 or MATH1902) Prohibitions: STAT3912, STAT3002, STAT3902, STAT3004, STAT3904 Assessment: One 2 hour exam, assignments and/or quizzes, and computer practical reports (100%) Associated degrees: B A, B A (Adv)(Hons), B A (Adv)(Hons), M B B S, B Med Sc, B Res Ec, B Sc, UG Study Abroad Program.

This course will introduce the fundamental concepts of analysis of data from both observational studies and experimental designs using classical linear methods, together with concepts of collection of data and design of experiments. First we will consider linear models and regression methods with diagnostics for checking appropriateness of models. We will look briefly at robust regression methods here. Then we will consider the design and analysis of experiments considering notions of replication, randomization and ideas of factorial designs. Throughout the course we will use the R statistical package to give analyses and graphical displays.

**STAT3912 Applied Linear Models (Advanced)**

Credit points: 6 Session: Semester 1 Classes: Three 1 hour lectures, one 1 hour tutorial and one 1 hour computer laboratory per week. Prerequisites: (STAT2912 or Credit in STAT2004 or Credit in STAT2012) and (MATH2061 or MATH2961 or MATH1902) Prohibitions: STAT3012, STAT3002, STAT3902, STAT3004, STAT3904 Assessment: One 2 hour exam, assignments and/or quizzes, and computer practical reports (100%) Associated degrees: B A, B A (Adv)(Hons), B A (Adv)(Hons), M B B S, B Med Sc, B Sc, UG Study Abroad Program.

This unit is essentially an Advanced version of STAT3012, with emphasis on the mathematical techniques underlying applied linear models together with proofs of distribution theory based on vector space methods. There will be 3 lectures per week in common with STAT3012 and some advanced material given in a separate advanced tutorial together with more advanced assessment work.