PUB HLTH 7074 - Introduction to Biostatistics
North Terrace Campus - Semester 1 - 2022
General Course Information
Course Code PUB HLTH 7074 Course Introduction to Biostatistics Coordinating Unit Public Health Term Semester 1 Level Postgraduate Coursework Location/s North Terrace Campus Units 3 Contact Up to 2 hours per week Available for Study Abroad and Exchange Y Incompatible PUB HLTH 7074OL, PUB HLTH 7074UAC, PUB HLTH 4274 Course Description 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 students an introduction to the discipline, an appreciation of a statistical perspective on information arising from the health arena and basic critical appraisal skills to assess the quality of research evidence.
Course Coordinator: Associate Professor Lynne GilesPhone: +61 8313 0234
Location: School of Public Health, Rundle Mall Plaza
The full timetable of all activities for this course can be accessed from Course Planner.
Course Learning OutcomesOn successful completion of this course, students will be able to:
1 Apply basic statistical concepts commonly used in Health and Medical 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)
Attribute 1: Deep discipline knowledge and intellectual breadth
Graduates have comprehensive knowledge and understanding of their subject area, the ability to engage with different traditions of thought, and the ability to apply their knowledge in practice including in multi-disciplinary or multi-professional contexts.
1, 2, 3
Attribute 2: Creative and critical thinking, and problem solving
Graduates are effective problems-solvers, able to apply critical, creative and evidence-based thinking to conceive innovative responses to future challenges.
2, 3, 4
Attribute 3: Teamwork and communication skills
Graduates convey ideas and information effectively to a range of audiences for a variety of purposes and contribute in a positive and collaborative manner to achieving common goals.
Attribute 4: Professionalism and leadership readiness
Graduates engage in professional behaviour and have the potential to be entrepreneurial and take leadership roles in their chosen occupations or careers and communities.
Attribute 5: Intercultural and ethical competency
Graduates are responsible and effective global citizens whose personal values and practices are consistent with their roles as responsible members of society.
Attribute 6: Australian Aboriginal and Torres Strait Islander cultural competency
Graduates have an understanding of, and respect for, Australian Aboriginal and Torres Strait Islander values, culture and knowledge.
Attribute 7: Digital capabilities
Graduates are well prepared for living, learning and working in a digital society.
1, 2, 3, 4
Attribute 8: Self-awareness and emotional intelligence
Graduates are self-aware and reflective; they are flexible and resilient and have the capacity to accept and give constructive feedback; they act with integrity and take responsibility for their actions.
The textbook for this course is: Bland M. Introduction to Medical Statistics. 4th edition. 2015; Oxford University Press, Oxford.
Copies are also available from the High Use desk in the Barr Smith Library. An electronic version of an earlier edition is also available from the Barr Smith Library. The content of the earlier edition is very similar to the 4th edition.
The Course Handbook will be made available to students before Week 1 of the semester and will be available in electronic form on MyUni. Supplementary material will also be placed on MyUni throughout the course, as required.
Recommended ResourcesThe 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 Vikki Langton.
Useful texts and references will be discussed by the course co-ordinators.
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/.
General information about University computer laboratories is available at http://www.adelaide.edu.au/technology/yourservices/learning-teaching/student-suites/
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 Ask Adelaide on 8313 5208 (University extension 35208) or the IT help desk on 8313 3000 (University extension 33000) for assistance with MyUni difficulties.
Course materials will be placed on MyUni. 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.
We assume that students access e-mail and that their address is the University of Adelaide student address that was assigned on enrolment. This is of the form: email@example.com 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 essential that students check their student e-mail and to log on to MyUni regularly.
Learning & Teaching Activities
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 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 tutorials and interactive learning sessions with directed learning to text, videos, and websites. The tutorials and interactive learning sessions are designed to develop and clarify topics covered in the readings and lectures. Tutorials are generally problem solving opportunities and students are required to complete as many questions as possible prior to revelation of solutions. Use of the discussion board will be encouraged and will support learning around the course materials. 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.
The information below is provided as a guide to assist students in engaging appropriately with the course requirements.
As a general rule in any post-graduate university course, students need to allow a minimum of eight to 12 hours per week. This means that, for Introduction to Biostatistics, in addition to engaging with the lecture material, students will need to set aside at least a further eight hours per week for reading around topics, completing tutorial and interactive learning session materials, participation in the online discussion board, and completion of 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 engage with all course materials as completion of readings alone will almost certainly not provide sufficient material to enable a pass.
Learning Activities Summary
Topic Lecture/Tutorial Introduction to Biostatistics and Descriptive Statistics Lecture: Introduction to Biostatistics and Descriptive Statistics. Tutorial: Administration of diagnostic tool and Descriptive statistics. Probability and Probability Distributions 1 Lecture: Probability concepts; Laws of probability. Tutorial: Further descriptive statistics Probability and Probability Distributions 2 Lecture: Probability distributions and sampling distributions. Tutorial: Probability and probability distributions. 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. Inferential Statistics 2 Lecture: Sample statistics and population parameters; confidence intervals. Tutorial: Setting up a statistical test, errors and power. 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. Comparison between Two Matched or Paired groups Lecture: Examples of matching and pairing; t-test for dependent samples. Tutorial: Inference for independent samples. Categorical Data Lecture: An introduction to the chi-square test of association. Tutorial: Inference for paired samples. Simple Linear Regression 1 Lecture: Method of least squares; definition of residuals. Tutorial: Calculating a chi-square test of association. Simple Linear Regression 2 Lecture: Assumptions of simple linear regression model; assessing assumptions. Tutorial: Simple linear regression. Correlation Lecture: Pearson’s correlation coefficient; inference and interpretation of correlation coefficients. Tutorial: More on simple linear regression and assumptions. Course Overview and Revision
Specific Course RequirementsN/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 Task Assessment Type Weighting Learning Outcome(s) being addressed Assignment 1: Summary Statistics Summative 10% 1, 3, 4 Assignment 2: Calculating probabilities and defining hypotheses Summative 20% 1, 3, 4 Assignment 3: Inferential Statistics Summative 30% 1-4 Examination Summative 40% 1-4
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.
Assessment Related Requirements
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 examination that will be scheduled in synchrony for all students. Further details concerning assignment submission and course policies on lateness and extensions will be provided in the Course Handbook.
Assignment 1: Descriptive statistics (10%)
The first assignment will assess students’ facility with calculating appropriate descriptive summary statistics of samples of data.
Assignment 2: Probability and hypotheses (20%)
The second assignment will assess students’ facility with using simple probability distributions and formulating null and alternative hypotheses.
Assignment 3: Inferential statistics (30%)
In this assignment, students will select and calculate appropriate test statistics based on scenarios drawn from the population health literature.
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.
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.
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.
If a student is dissatisfied with an assessment grade they should follow the Student Grievance Resolution Process <https://www.adelaide.edu.au/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.
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 Access Adelaide.
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.
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This section contains links to relevant assessment-related policies and guidelines - all university policies.
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