成人大片

Course Coordinator: Dr Murthy Mittinty
Phone: +61 8313 0961
Email: murthy.mittinty@adelaide.edu.au 
Location: Level 4, Rundle Mall Plaza, North Terrace

Timetable details are located on MyUni.

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.

The textbook for this course is: Bland M.  Introduction to Medical Statistics.  4th edition.  2015; Oxford University Press, Oxford. 

A copy of the textbook may be accessed via the High Use collection at the Barr Smith Library.

Supplementary reading material and course notes will also be placed on MyUni.

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/.

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.

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.

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.

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

N/A

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

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

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

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.