Unit Outline

This unit offers an introduction to the fundamental concepts of biostatistics, providing a background in descriptive and analytical methods that are used to estimate associations between variables. This unit covers statistical theory, data entry and manipulation methods, data summarising, basic methods of association, and regression modelling. With the basic tools found within this course, students will be able to enter, manipulate, and check the validity of data, and use statistical software to analyse and interpret results. The analytical methods used here will form the foundation of research methods in epidemiology and health services research.

Intended Learning Outcomes

As per the Assessment and Results Policy 1.3, your results will reflect your achievement against specified learning outcomes.

On completion of this unit, you will be able to:


1	Apply your knowledge of statistical theory to produce summary statistics for health research data.
2	Implement data management guidelines for health research data.
3	Manage and analyse health research data using a statistical package.
4	Identify and apply appropriate statistical methods to analyse health research data.
5	Interpret, summarise and communicate the results of a statistical analyses.

Alterations as a result of student feedback

In response to student feedback and our observations of barriers to learning, we have made the following changes to the unit. We have updated the MyLO template to be consistent with other MPH units and to improve the delivery of unit content by provider a clearer structure for the material to be covered each week. We have added interactive R coding examples to introduce students to coding via a workspace that provides immediate feedback on errors and access to the coding solution. We have restructured the weekly tutorials to include one R coding session (instead of two) and one statistical theory session. We continue our ongoing revision of the content to expand and clarify topics that students find difficult.

How will I be Assessed?

For more detailed assessment information please see MyLO.

Assessment schedule


ASSESSMENT TASK #	ASSESSMENT TASK NAME	DATE DUE	WEIGHT	LINKS TO INTENDED LEARNING OUTCOMES
Assessment Task 1:	Take-home tests	Week 2	50 %	LO1, LO2, LO3, LO4
Assessment Task 2:	Statistical report 1	Week 9	10 %	LO5
Assessment Task 3:	Statistical report 2	Week 14	40 %	LO1, LO2, LO3, LO4, LO5

Assessment details

Assessment Task 1: Take-home tests

Task Description:

There are five online tests delivered as quizzes in MyLO; two tests for Module 1, and one test for each of modules 2-4. Each test will consist of 10-15 multiple choice and short answer questions. They are open-book tasks, and there is no time restriction for completion as long as they are submitted by the due date.
Online tests are due in weeks 2, 4, 6, 8 and 12

Task Length:

Due Date:

Week 2

Weight:

50 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Apply knowledge of statistical theory and methods to provide correct answers to quiz questions.	LO1, LO2, LO3, LO4

Assessment Task 2: Statistical report 1

Task Description:

Interpretation and communication of results from a statistical analysis.

Task Length:

Short answer responses to interpret the results presented for each question. Expected overall length 500-1,000 words.

Due Date:

Week 9

Weight:

10 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Interpret descriptive statistics, explaining the relationships between exposure variables and a continuous outcome variable (25%)	LO5
2	Interpret the results of univariable regression models, explaining the estimated associations of exposures with a continuous outcome variable (35%)	LO5
3	Interpret the results of a multivariable regression model, explaining the adjusted association of the primary exposure with a continuous outcome variable (25%)	LO5
4	Interpret regression diagnostics to assess the fit of the model (15%)	LO5

Assessment Task 3: Statistical report 2

Task Description:

Apply statistical knowledge to run appropriate statistical analyses using R code for a health dataset, and present and interpret the results of the analyses.

Task Length:

Approx. 200-250 lines of code in an R script file. Maximum of 1200 words for the interpretation of results.

Due Date:

Week 14

Weight:

40 %

CRITERION #

CRITERION

MEASURES INTENDED

LEARNING OUTCOME(S)


1	Prepare an annotated R script file to import and analyse data (10%)	LO2, LO3
2	Produce descriptive statistics for individual variables that are appropriate for the scale of measurement (binary, categorial, continuous) using R code (20%)	LO1, LO3
3	Fit univariable and multivariable regression models for a continuous and binary outcome variables using R code (20%)	LO3, LO4
4	Present the descriptive statistics and regression models in formatted tables suitable for publication (10%)	LO5
5	Provide a brief summary of the descriptive statistics and interpretation of the regression analyses (40%)	LO5

How your final result is determined

To pass this unit, you need to demonstrate attainment of each of the Intended Learning Outcomes and attain an overall pass (50%) for the unit. Your final result will be determined as the weighted average of the numerical scores given to assessment tasks. Any student who attains an overall passing grade but who has failed one ILO will be given a supplementary assessment opportunity to demonstrate their attainment of the relevant ILO.

Submission of assignments

Where practicable, assignments should be submitted to an assignment submission folder in MYLO. You must submit assignments by the due date or receive a penalty (unless an extension of time has been approved by the Unit Coordinator). Students submitting any assignment in hard copy, or because of a practicum finalisation, must attach a student cover sheet and signed declaration for the submission to be accepted for marking.

Academic integrity

Academic integrity is about acting responsibly, honestly, ethically, and collegially when using, producing, and communicating information with other students and staff members.

In written work, you must correctly reference the work of others to maintain academic integrity. To find out the referencing style for this unit, see the assessment information in the MyLO site, or contact your teaching staff. For more detail about Academic Integrity, see Important Guidelines & Support.

Requests for extensions

If you are unable to submit an assessment task by the due date, you should apply for an extension.

A request for an extension should first be discussed with your Unit Coordinator or teaching support team where possible. A request for an extension must be submitted by the assessment due date, except where you can provide evidence it was not possible to do so. Typically, an application for an extension will be supported by documentary evidence: however, where it is not possible for you to provide evidence please contact your Unit Coordinator.

The Unit Coordinator must notify you of the outcome of an extension request within 3 working days of receiving the request.

Late penalties

Assignments submitted after the deadline will receive a late penalty of 5% of the original available mark for each calendar day (or part day) that the assignment is late. Late submissions will not be accepted more than 10 calendar days after the due date, or after assignments have been returned to other students on a scheduled date, whichever occurs first. Further information on Late Penalties can be found on the Assessments and Results Procedure.

Review of results and appeals

You are entitled to ask for a review of the marking and grading of your assessment task if there is an irregularity in the marking standards or an error in the process for determining the outcome of an assessment. Details on how to request a review of a mark for an assignment are outlined in the Review and Appeal of Academic Decisions Procedure.