Year
2021Credit points
10Campus offering
No unit offerings are currently available for this unitPrerequisites
NilUnit rationale, description and aim
This unit provides an introduction to the presentation and analysis of data used in health science research. It presents a perspective on the issues of data management as a basis for the application of these issues to specific research problems. Common principles for the management of quantitative data are explored. Some opportunity for specialisation in particular components of data management specific to the needs of the student's developing research problem will be offered. The unit aims to increase students' knowledge and skill in aspects of data management appropriate to honours research.Learning outcomes
To successfully complete this unit you will be able to demonstrate you have achieved the learning outcomes (LO) detailed in the below table.
Each outcome is informed by a number of graduate capabilities (GC) to ensure your work in this, and every unit, is part of a larger goal of graduating from ACU with the attributes of insight, empathy, imagination and impact.
Explore the graduate capabilities.
On successful completion of this unit, students should be able to:
LO1 - Demonstrate an advanced knowledge of the principles and basic concepts of data management from collection to analysis (GA8, GA9)
LO2 - Select and apply these to numerical forms of data (GA4, GA10)
LO3 - Identify appropriate data analysis methods for a given research design (GA4)
LO4 - Evaluate statistical differences and associations with numerical data (GA4, GA10)
Graduate attributes
GA4 - think critically and reflectively
GA8 - locate, organise, analyse, synthesise and evaluate information
GA9 - demonstrate effective communication in oral and written English language and visual media
GA10 - utilise information and communication and other relevant technologies effectively.
Content
- The content of the unit may include but is not limited to:
- Introduction to basic statistics
- Data and measurement scales
- Relative frequency
- Classification of variables
- Graphic display of data
- Measures of Central Tendency and Variability
- Introduction to SPSS
- Probability distributions
- The Normal Distribution
- The Standard Normal Distribution
- Inferential statistics: Estimation and testing
- Hypothesis testing
- Type I, Type II errors
- Power
- P value
- Student t test (independent and dependent samples)
- Chi-square test
- Analysis of variance (ANOVA)
- ANOVA with repeated measurements
- Correlation and simple linear regression
Learning and teaching strategy and rationale
This unit is offered fully online to provide flexibility and self-pacing options to students. This unit runs in intensive mode over the first six weeks of the teaching semester, allowing students to complete the unit mid-semester and commence work on their research study in a timely way.
Assessment strategy and rationale
A range of assessment procedures will be used to meet the unit learning outcomes and develop graduate attributes consistent with University assessment requirements. The unit assessment provides opportunities for students to explore statistical methodologies and analyses appropriate to their project. Students will learn statistical skills that align with their research project and contribute to their thesis.
Overview of assessments
| Brief Description of Kind and Purpose of Assessment Tasks | Weighting | Learning Outcomes | Graduate Attributes |
|---|---|---|---|
Assignment 1 This assignment allows students to demonstrate their ability to set up a statistical test, appropriately state the null and alternative hypothesis and use SPSS skills to solve statistical problems. | 20% | LO1, LO2, LO3 | GA4, GA8, GA9, GA10 |
Assignment 2 This assignment allows students to demonstrate their ability to select and apply an appropriate statistical test for various real life situations. | 40% | LO1, LO2, LO3, LO4 | GA4, GA8, GA9, GA10 |
Assignment 3 This assessment task requires students to write the first draft of their quantitative methods chapter. | 40% | 40% | GA4, GA8, , GA9 |
Representative texts and references
Barton, B. & Peat, J. (2014). Medical Statistics: A Guide to SPSS, Data Analysis and Critical Appraisal. (2nd ed.) Melbourne: Blackwell Publishing
Baumgartner, T.A. & Hensley, L.D. (2013). Conducting & Reading Research in Kinesiology (5th ed.). New York: McGraw-Hill.
Coakes, S. & Steed, L. (2013). SPSS Analysis without anguish. Version 20.0. for Windows Brisbane: John Wiley & Sons.
Hirsch, R.P. & Riegelman, R.K. (1992). Statistical First Aid: Interpretation of Health Research Data. Boston, Mass: Blackwell Scientific Publications
Portney, L. G. & Watkins, M. P. (2015). Foundations of clinical research: applications to practice (3rd ed). Upper Saddle River, New Jersey: Prentice Hall Health.
Tabachnick, B. G. & Fidell, L. S. (2001). Using Multivariate Statistics (4th edition). Boston: Allyn and Bacon.