PUB HLTH 7104 - Biostatistics

North Terrace Campus - Semester 2 - 2017

This course is designed to suit students requiring a high degree of self-sufficiency in the collection, analysis and interpretation of data. The topics will include non-parametric statistical methods, linear models, logistic regression, Generalized Linear Models and Poisson regression, and survival analysis. A central feature of the course will be instruction in the use of statistical packages on computers, primarily Stata. Emphasis will be placed on data management and manipulation, practical application of statistical skills to real data sets and interpretation of results

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Course Details

Course Code	PUB HLTH 7104
Course	Biostatistics
Coordinating Unit	Public Health
Term	Semester 2
Level	Postgraduate Coursework
Location/s	North Terrace Campus
Units	3
Contact	Up to 3 hours per week
Available for Study Abroad and Exchange	N
Prerequisites	Credit standard in PUB HLTH 7074 or PUB HLTH 7074OL
Restrictions	Available to Grad Cert, Grad Dip, MPH & MHEP students only
Assessment	Data Management Exercise, Statistical Analysis Project

Course Staff

Course Coordinator: Associate Professor Lynne Giles

Course Coordinator: Associate Professor Lynne Giles
Phone: +61 8313 0234
Email: lynne.giles@adelaide.edu.au
Location: Level 7, 178 North Terrace

Student & Program Support Services Hub
Email: askhealthsc@adelaide.edu.au
Phone: +61 8313 0273

Course Timetable

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

Course Learning Outcomes

On successful completion of this course, students will be able to:

1	Manage and manipulate data efficiently and effectively;
2	Apply a range of simple and complex statistical analysis techniques commonly used in Health Sciences appropriately;
3	Demonstrate statistical reasoning skills correctly and contextually;
4	Interpret results of statistical analyses in written summaries; and
5	Use the statistical software package 'Stata' proficiently to conduct data manipulation and statistical analyses.

University Graduate Attributes

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

University 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)	1, 2
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	2, 3, 4
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	3, 4
Career and leadership readiness technology savvy professional and, where relevant, fully accredited forward thinking and well informed tested and validated by work based experiences	1, 5
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	N/A
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	3, 4

Learning Resources

Required Resources

The textbook for this course is: Armitage P, Berry G, Matthews JNS. Statistical Methods in Medical Research (4th edition). 2008; Wiley-Blackwell, London.

An electronic version of the textbook may be accessed for free via the Barr Smith Library.

Supplementary reading material will also be placed on MyUni.

Recommended Resources

The 成人大片 recently introduced Project ADAPT: http://www.adelaide.edu.au/its/adapt. ADAPT is any Device, any Place and Time. Students can access Stata 13 (and other software including R, SPSS and MATLAB) from their home computers and their portable devices (such as smartphones and tablets) via Project ADAPT. See the website above for more details.

Students wishing to purchase their own copy of Stata will need to do so through Survey Design and Analysis Services (the Australian distributor of Stata; see http://www.survey-design.com.au/gradplan.html). There are several options in their Grad Plan packages; price is determined by the length of licence, with prices ranging from ~$100 to $200. Further details will be discussed in class.

Useful texts and references will be discussed in class by the course co-ordinator. A very important resource for students encountering any difficulties with mathematics or statistics at the 成人大片 is the Maths Learning Centre based on Level 3 East of Hub Central, North Terrace Campus. For details go to http://www.adelaide.edu.au/mathslearning/.

Online Learning

Computers
General information about University computer laboratories is available at http://www.adelaide.edu.au/technology/yourservices/learning-teaching/student-suites/

MyUni
As an enrolled student, you will have access to the University’s on-line teaching facilities. This is an implementation of the Blackboard system called MyUni. MyUni is accessible from the 成人大片’s home-page: www.adelaide.edu.au . You will need your student login name and a password.

If you do not have access, then either you are not enrolled or the administrators of MyUni do not know of your enrolment. Please call Ask Adelaide on 8313 5208 (University extension 35208) or the IT help desk on 8313 3000 (University extension 33000) for assistance with MyUni difficulties.

Selected documentation for this course will be placed on MyUni including lecture overheads, lecture recordings, computer practical documentation, and data sets. Note also that Announcements about a course are often made on the relevant page of the MyUni site for the course. For example, notifications of a change in lecture venue, updates on availability of course material etc. will be made on the MyUni site.

Email
Students are assumed to have access to e-mail and that the address is the 成人大片 student address that was assigned on enrolment. This is of the form: firstname.lastname@student.adelaide.edu.au A notice to a student by e-mail is considered to have been received and read by the student unless there is a transmission error and the postmaster bounces the message back to us. As discussed above, the Announcements page of the MyUni site for this course will also display relevant notices from time to time, so it is in students’ interests to check student e-mail and to log on to MyUni regularly.

Learning & Teaching Modes

There are a number of teaching and learning modes in this course. The course lectures provide basic factual information and concepts in biostatistics. Due to the limited timeframe, not everything will be covered in lectures. Lectures are intended to supplement material covered in the readings. Lectures will be supported by interactive practicals which are designed to develop software skills and clarify topics covered in the readings and lectures. These are problem solving sessions and students are required to prepare for these sessions. Assignments provide an opportunity to undertake exploratory and in-depth analysis of some key concepts introduced in the course, and demonstrate their understanding of biostatistical concepts.

Workload

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

As a general rule in any university course, you will need to allow a minimum of three independent study hours for every hour undertaken in formal class work contact. This means that, for Biostatistics, you will need to set aside at least further nine hours per week for reading around topics, preparation for practicals, and submitting your assignments. You are urged to bear this in mind when planning your university timetable, particularly if you are also engaged in paid employment. In our experience, students may not be able to demonstrate their full capacity if they are working full-time and studying full-time. Students are expected to attend all lectures and practicals as completion of readings alone will almost certainly not provide sufficient material to enable a pass.

Learning Activities Summary

Topic	Lecture/Practical
Managing data	Lecture: Introduction, data sets, and statistical systems Practical: Getting started with Stata
Non-parametric statistical methods	Lecture: Exploratory data analysis, Sign test, Wilcoxon rank-sum test Practical: Manipulating data and working with dates in Stata
Non-parametric statistical methods	Lecture: Wilcoxon rank-sum test, Wilcoxon signed-rank test Practical: Assessing normality and non-parametric methods in Stata
Linear Models 1	Lecture: Simple linear regression and regression diagnostics Practical: Linear regression and regression diagnostics
Linear Models 2	Lecture: Multiple linear regression and model assumptions Practical: Fitting a multiple linear regression model
Linear Models 3	Lecture: Analysis of covariance and model assumptions Practical: Anova and ancova in Stata
Analysis of binary responses 1	Lecture: Measure of effect with binary data: Odds ratios, Mantel-Haenszel Odds ratios Practical: The Epitab suite
Analysis of binary responses 2	Lecture: Simple and multiple logistic regression Practical: Logistic regression models
Survival analysis 1	Lecture: Introduction to time to event data and life tables Practical: Life tables and survivorship functions
Survival analysis 2	Lecture: Introduction to Cox proportional hazards regression models Practical: Fitting a Cox model in Stata
Survival analysis 3	Lecture: Assessing the assumptions of Cox proportional hazards regression models Practical: Stratified Cox proportional hazards models
Generalized Linear Models	Lecture: Introduction to common Generalized Linear Models Practical: Poisson regression and glm

Specific Course Requirements

N/A

Small Group Discovery Experience

N/A

The University'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 Task	Assessment Type	Weighting	Learning Outcome(s) being addressed
Multiple choice quiz: Interpreting Stata output	Summative	5%	2, 3, 4
Data management and interpretation exercise	Summative	35%	1-5
Statistical analysis project	Summative	50%	1-5
Engagement in lectures and practicals	Formative and summative	10%	3, 4

Assessment Related Requirements

To pass this course, you must achieve 50% overall, and a pass (50% or more) in the Statistical Analysis Project.

Assessment Detail

All assessment tasks will be distributed via hardcopy in lectures. All assessment tasks will be assessed according to the University's M10 mark scheme.

Submission

Extensions
All extensions for assignments must be requested, at the latest, by the last working day before the due date of submission. Extensions will generally be granted only on medical or genuine compassionate grounds. Supporting documentation must be provided at the time a student requests an extension. Without documentation, extensions will not be granted. Late requests for extension will neither be accepted nor acknowledged.

Only the Course Co-ordinator(s) may grant extensions.

Supporting documentation will be required when requesting an extension. Examples of documents that are acceptable include: a medical certificate that specifies dates of incapacity, a police report (in the case of lost computers, car & household theft etc.), a letter from a Student Counsellor, Education and Welfare Officer (EWO) or Disability Liaison Officer that provides an assessment of compassionate circumstances, or a letter from an independent external counsellor or appropriate professional able to verify the student’s situation. The length of any extension granted will take into account the period and severity of any incapacity or impact on the student. Extensions of more than 10 days will not be granted except in exceptional circumstances.

Late submission
Marks will be deducted when assignments for which no extension has been granted are handed in late.

All assignments, including those handed in late, will be assessed on their merits. In the case of late assignments where no extension has been granted, 5 percentage points of the total marks possible per day will be deducted. If an assignment that is 2 days late is awarded 65% on its merits, the mark will then be reduced by 10% (5% per day for 2 days) to 55%. If that same assignment is 4 days late, the mark will be reduced by 20% (5% per day for 4 days) to 45%, and so on.

The School of Public Health reserves the right to refuse to accept an assignment that is more than 7 days late.

Assignments submitted after the due date may not be graded in time to be returned on the listed return dates.

Students submitting examinable written work who request (and receive) an extension that takes them beyond the examination period are advised that there is no guarantee that their grades will be processed in time to meet usual University deadlines.

Resubmission
If a student is dissatisfied with an assessment grade they should follow the Student Grievance Resolution Process </student/grievance/process/>. Students who are not satisfied with a particular assessment result should raise their concerns with Course Co-ordinator(s) in the first instance. This must be done within 10 business days of the date of notification of the result. Resubmission of any assignment is subject to the agreement of the Course Co-ordinator(s) and will only be permitted for the most compelling of reasons.

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

The University places a high priority on approaches to learning and teaching that enhance the student experience. Feedback is sought from students in a variety of ways including on-going engagement with staff, the use of online discussion boards and the use of Student Experience of Learning and Teaching (SELT) surveys as well as GOS surveys and Program reviews.

SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.
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.

The 成人大片 is committed to regular reviews of the courses and programs it offers to students. The 成人大片 therefore reserves the right to discontinue or vary programs and courses without notice. Please read the important information contained in the disclaimer.

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

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