Course Coordinator: Dr Lynne Giles
Phone: +61 8313 0234
Email: lynne.giles@adelaide.edu.au
Location: Room 7-09, 178 North Terrace

Learning and Teaching Team
Phone: +61 8313 2128
Email: postgrad_enq@adelaide.edu.au
Location: Level 7, 178 North Terrace

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

1	Apply basic statistical concepts commonly used in Health Sciences;
2	Use basic analytical techniques to generate results;
3	Interpret results of commonly used statistical analyses in written summaries; and
4	Demonstrate statistical reasoning skills correctly and contextually.

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.

The Barr Smith Library is an important resource for any student of public health and in Orientation Week tours of the Library are arranged. The librarian with responsibility for public health is Maureen Bell.

Useful texts and references will be discussed in class by the lecturers.

A very important resource for students encountering any difficulties with mathematics or statistics at the University of Adelaide 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/its/student_support/labs/

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 University of Adelaide’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 the Student Centre on 8313 5208 (Uni extension 35208) or the MyUni help desk on 8313 3335 (Uni extension 33335) for assistance with MyUni difficulties.

Selected documentation for this course will be placed on MyUni including lecture overheads, lecture recordings, and tutorials. 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
We assume that you have access to e-mail and that your address is the University of Adelaide student address that was assigned to you 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 your interest to check your 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 an introduction to 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 tutorials which are designed to develop and clarify topics covered in the readings and lectures. These are generally problem solving sessions and students are required to complete as many questions as possible prior to their allocated tutorial. Assignments provide an opportunity to undertake exploratory and in-depth analysis of some key concepts introduced in the course. Finally, the exam will assess the extent to which students have developed their biostatistical understanding through the course.

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 Introduction to Biostatistics, you will need to set aside at least a further six hours per week for reading around topics, preparation for tutorials, 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 tutorials as completion of readings alone will almost certainly not provide sufficient material to enable a pass.

Important notes:
a) Students are expected to complete readings prior to the lecture for which they are assigned and, where appropriate, to have worked through tutorial problems before the scheduled tutorial, with the exception of the tutorial in week 1.
b)
c) Students are expected to attend all lectures and tutorials as completion of readings alone will almost certainly not provide sufficient material to enable a pass.

Week	Topic	Lecture/Tutorial
Week 1	Introduction to Biostatistics and Descriptive Statistics	Lecture: Introduction to Biostatistics and Descriptive Statistics. Tutorial: Administration of diagnostic tool and Descriptive statistics.
Week 2	Probability and Probability Distributions 1	Lecture: Probability concepts; Laws of probability. Tutorial: Further descriptive statistics
Week 3	Probability and Probability Distributions 2	Lecture: Probability distributions and sampling distributions. Tutorial: Probability and probability distributions.
Week 4	Internal Statistics 1	Lecture: Null and alternative hypotheses and how to set up a statistical test. Tutorial: The binomial probability distribution and the Normal distribution.
Week 5	Internal Statistics 2	Lecture: Sample statistics and population parameters; confidence intervals. Tutorial: Setting up a statistical test, errors and power.
Week 6	Comparison between two independent groups	Lecture: Conducting a z-test; the t-distribution; conducting a t-test for independent samples. Tutorial: Calculation of a confidence interval.
Week 7	Comparison between two matched or paired groups	Lecture: Examples of matching and pairing; t-test for dependent samples. Tutorial: Inference for independent samples.
Week 8	Categorical data	Lecture: An introduction to the chi-square test of association. Tutorial: Inference for paired samples.
Week 9	Simple linear regression 1	Lecture: Method of least squares; definition of residuals. Tutorial: Calculating a chi-square test of association.
Week 10	Simple linear regression 2	Lecture: Assumptions of simple linear regression model; assessing assumptions. Tutorial: Simple linear regression.
Week 11	Correleation	Lecture: Pearson’s correlation coefficient; inference and interpretation of correlation coefficients. Tutorial: More on simple linear regression and assumptions.
Week 12	Course overview and revision

Assessment Task	Assessment Type	Weighting	Learning Outcome(s) being addressed
Assignment 1: Descriptive Statistics	Summative	20%	1, 3, 4
Assignment 2: Inferential Statistics	Summative	20%	1-4
Examination	Summative	60%	1-4

Supplementary Examinations
In the event that a student does not pass, a supplementary examination (which may be viva voce)
and/or further set work (at the discretion of the course co-ordinators) may be offered. A student
offered such supplementary assessment may obtain one of two grades: Pass (with a maximum score of 50% recorded) or Fail. The mark shall be awarded on either (i) the results of the supplementary assessment only, or (ii) the combined results of the course assignments and supplementary assessment, whichever advantages the student most. In the event of a Fail after supplementary assessment, the entire course must be repeated.

Editing Guidelines
Assignments and written work should, whenever feasible, be typed or word-processed, although work comprising algebraic notation is acceptable in handwritten form if neat and legible.

To pass this course, a student must submit both assignments and score at least 50% overall (assignments and examination).

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

Assignments can only be submitted in hardcopy form either to someone at Reception or through the slot in the locked box at the Discipline of Public Health, Level 7, 178 North Terrace. The appropriate cover sheet must be attached to each assignment. These coversheets are available through MyUni. Each student submitting an assignment must also sign and date the designated class list (for this course and this assignment) which will be available at Reception. Assignments must be submitted by 4.00pm on the due date. The locked box will be emptied every day at this time.

Multiple pages should be stapled at the top left hand corner, irrespective of whether a protective plastic sleeve is used. Each page should be numbered and the total number of pages should appear on each page (e.g. “page 2 of 4” or “2/4”). The first page should bear the student’s name and student number; each subsequent page should bear, at least, the student’s initials. It is prudent to keep a photocopy of your assignment.

An assignment may not be submitted by e-mail or by fax and should not be given to lecturers or tutors in an ad hoc fashion at the time of lectures or tutorials. Marked assignments can be collected from the Discipline of Public Health.

Extensions
Must be requested, at the latest, by the last working day before the due date of submission.
Will generally be granted only on medical or genuine compassionate grounds.
Only the course coordinator(s), or a person authorised by him or her, may grant extensions.
Documentary supporting evidence such as a medical certificate or a police report (in the case of lost computers, car & household theft etc.) will usually be required when requesting an extension.

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 finalised “in time for graduation” for post-graduate courses or “in time to meet usual University deadlines”.

Lateness
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, marks will then be deducted from the mark awarded, at the rate of 5 percentage points of the total possible per day. e.g. If an assignment which is 2 days late is awarded 65% on its merits, the mark will then be reduced by 10 (5 marks per day for 2 days) to 55%. If that same assignment is 4 days late its mark will be reduced by 20 (5 marks per day for 4 days) to 45% etc.

The Discipline reserves the right to refuse to accept an assignment that is more than 7 days late.