PUB HLTH 7074OL - Introduction to Biostatistics

Online - Semester 1 - 2015

Biostatistics is the application of statistical methods (summarising data and drawing valid inferences based on limited information) to biological systems, more particularly, to humans and their health problems. This course deals with statistical concepts and terminology and basic analytic techniques. The purpose of the course is to give public health and occupational health workers an introduction to the discipline, an appreciation of a statistical perspective on information arising from the health arena and basic critical appraisal skills to enable graduates to assess the quality of research evidence.

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Course Details

Course Code	PUB HLTH 7074OL
Course	Introduction to Biostatistics
Coordinating Unit	Public Health
Term	Semester 1
Level	Postgraduate Coursework
Location/s	Online
Units	3
Contact	Online
Available for Study Abroad and Exchange	N
Incompatible	PUB HLTH 7074

Course Staff

Course Coordinator: Dr Amy Salter
Phone: +61 8313 4619
Email: amy.salter@adelaide.edu.au
Location: Level 8 Hughes Building

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

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

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	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.

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)
The ability to locate, analyse, evaluate and synthesise information from a wide variety of sources in a planned and timely manner.	1,2,3
An ability to apply effective, creative and innovative solutions, both independently and cooperatively, to current and future problems.	2,3,4

Learning Resources

Required Resources

The textbook for this course is: Armitage P, Berry G, Matthews JNS. Statistical Methods in

Medical Research (4th edition). 2002 (2008 for electronic edition); Wiley-Blackwell, London.

Course Handbook and Study Guides will be made available to students before Week 1 of the semester and will be available in electronic form on MyUni.

Please note: an electronic version of the textbook may be accessed for free via the Barr Smith Library. It is accessed via the ‘ebrary’ portal which will be discussed in Week 1 on Blackboard in MyUni. Supplementary reading material may also be placed on MyUni throughout the course, as required.

Recommended Resources

N/A

Online Learning

MyUni will provide the online learning system for students via
Once students have sucessfully enrolled in this course they can access the MyUni site where they can access lectures, tutorials, assignments, join discussion forums and link up with the course co-ordinators and fellow students.

Learning & Teaching Modes

There are a number of teaching and learning modes in this course. The online course lectures provide basic factual information and concepts in biostatistics. Lectures are intended to supplement material covered in the study guides and readings. Lectures will be supported by online tutorials with directed learning to text, videos, and websites. The tutorials 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 the Blackboard discussion date. 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.

Workload

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

Consistent of 3 assignments plus an examination and weekly readings.

Learning Activities Summary

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	Inferential 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	Inferential Statistics 2	Lecture: Sample statistics and population parameters, confidence intervals Tutorials: 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	Correlation	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
Week 13	Self directed study for exam revision

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	Task Type	Weighting	Learning course objective(s) being addressed
Assignment 1: Summary statistics	Summative	5%	1, 3, 4
Assignment 2: Calculating probabilities and defining hypotheses	Summative	15%	1, 3, 4
Assignment 3: Inferential statistics	Summative	20%	1-4
Examination	Summative	60%	1-4

Assessment Related Requirements

N/A

Assessment Detail

There will be three assignments and an examination in this course. All assignments will be posted on MyUni at least 2 weeks prior to the date of submission. Students will be required to participate in an on-line, open book examination for a period of two hours that will be scheduled in synchrony for all students.

Assignment 1: Descriptive statistics (5%)
The first assignment will assess students’ facility with calculating appropriate descriptive summary statistics of samples of data. Due at end of Week 3 of Semester 1.

Assignment 2: Probability and hypotheses (15%)
The second assignment will assess students’ facility with using simple probability distributions and formulating null and alternative hypotheses.
Due at end of Week 6 of Semester 1.

Assignment 3: Inferential statistics (20%)
In this assignment, students will select and calculate appropriate test statistics based on scenarios drawn from the population health literature.
Due at end of Week 12 of Semester 1.

Examination (60%)
The students will be required to demonstrate their statistical reasoning skills by way of calculating descriptive statistics, formulating null and alternative hypotheses, performing inferential statistical tests, and interpreting the results of their calculations. Scheduled in Semester 1 examination period.

Submission

Information will be provided on MyUni

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.
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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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Maintained by:	Course Outlines Administrator

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