BIOSTATS 6007EX - Categorical Data & Generalised Linear Models

External - Semester 2 - 2017

The aim of this course is to enable students to use generalised linear models (GLMs) and other methods to analyse categorical data with proper attention to the underlying assumptions. There is an emphasis on the practical interpretation and communication of results to colleagues and clients who may not be statisticians. The content includes: introduction to and revision of conventional methods of contingency tables especially in epidemiology; odds ratios and relative risks; chi-squared tests for independence; Mantel-Haenszel methods for stratified tables; and methods for paired data. The exponential family of distributions includes: generalised linear models (GLMs), and parameter estimation for GLMs; inference for GLMs-including the use of score, Wald and deviance statistics for confidence intervals and hypothesis tests, and residuals; binary variables and logistic regression models-including methods for assessing model adequacy; nominal and ordinal logistic regression for categorical response variables with more than two categories; and count data, Poisson regression and log-linear models.

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Course Details

Course Code	BIOSTATS 6007EX
Course	Categorical Data & Generalised Linear Models
Coordinating Unit	Public Health
Term	Semester 2
Level	Postgraduate Coursework
Location/s	External
Units	3
Contact	Online
Available for Study Abroad and Exchange	N
Prerequisites	BIOSTATS 6000EX, BIOSTATS 6001EX, BIOSTATS 6003EX & BIOSTATS 6005EX
Corequisites	BIOSTATS 6006EX
Restrictions	Available to Grad Cert, Grad Dip, M Biostatistics students only
Assessment	Three written assignments (35%, 35%, 30%)

Course Staff

Course Coordinator: Dr Amy Salter

Course Coordinator : Dr Amy Salter
Phone: +61 8313 4619
Email: amy.salter@adelaide.edu.au
Location: Level 11, 178 North Terrace

Course Timetable

The full timetable of all activities for this course can be accessed from .

Course Learning Outcomes

最新糖心Vlog Graduate Attributes

This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

最新糖心Vlog Graduate Attribute	Course Learning Outcome(s)
Deep discipline knowledge informed and infused by cutting edge research, scaffolded throughout their program of studies acquired from personal interaction with research active educators, from year 1 accredited or validated against national or international standards (for relevant programs)	.
Critical thinking and problem solving steeped in research methods and rigor based on empirical evidence and the scientific approach to knowledge development demonstrated through appropriate and relevant assessment	.
Teamwork and communication skills developed from, with, and via the SGDE honed through assessment and practice throughout the program of studies encouraged and valued in all aspects of learning	.
Career and leadership readiness technology savvy professional and, where relevant, fully accredited forward thinking and well informed tested and validated by work based experiences	.
Intercultural and ethical competency adept at operating in other cultures comfortable with different nationalities and social contexts able to determine and contribute to desirable social outcomes demonstrated by study abroad or with an understanding of indigenous knowledges	.
Self-awareness and emotional intelligence a capacity for self-reflection and a willingness to engage in self-appraisal open to objective and constructive feedback from supervisors and peers able to negotiate difficult social situations, defuse conflict and engage positively in purposeful debate	.

Learning Resources

Required Resources

Recommended Resources

Online Learning
Learning & Teaching Activities

Learning & Teaching Modes

Workload

The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

Learning Activities Summary

Specific Course Requirements

Small Group Discovery Experience

The 最新糖心Vlog's policy on Assessment for Coursework Programs is based on the following four principles:

Assessment must encourage and reinforce learning.
Assessment must enable robust and fair judgements about student performance.
Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
Assessment must maintain academic standards.

Assessment Summary

Assessment Related Requirements

Assessment Detail

Submission

Course Grading

Grades for your performance in this course will be awarded in accordance with the following scheme:

M10 (Coursework Mark Scheme)
Grade	Mark	Description
FNS		Fail No Submission
F	1-49	Fail
P	50-64	Pass
C	65-74	Credit
D	75-84	Distinction
HD	85-100	High Distinction
CN		Continuing
NFE		No Formal Examination
RP		Result Pending

Further details of the grades/results can be obtained from Examinations.

Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

Final results for this course will be made available through .

Student Feedback

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Student Support
Policies & Guidelines
This section contains links to relevant assessment-related policies and guidelines - all university policies.
Fraud Awareness

Students are reminded that in order to maintain the academic integrity of all programs and courses, the university has a zero-tolerance approach to students offering money or significant value goods or services to any staff member who is involved in their teaching or assessment. Students offering lecturers or tutors or professional staff anything more than a small token of appreciation is totally unacceptable, in any circumstances. Staff members are obliged to report all such incidents to their supervisor/manager, who will refer them for action under the university's student鈥檚 disciplinary procedures.

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Authorised by:	Deputy Vice-Chancellor and Vice-President (Academic)
Maintained by:	Course Outlines Administrator

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