Design and Analysis for Neurosciences A (NEUR90007)
Graduate courseworkPoints: 12.5On Campus (Parkville)
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Overview
| Availability | March |
|---|---|
| Fees | Look up fees |
This subject is an intensive 5 consecutive day program, introducing the main principles of scientific method, research design and scientific study validity using a structured approach. This subject will introduce the basic concepts of study design and layered topic-specific exercises and/or project-specific exercises. Students are taken through the initial ”building blocks” that form the basis for a sound research study. This includes:
- fundamentals of scientific methods;
- study validity;
- sampling;
- measurement;
- establishing cause and effect relationship;
- making statistical conclusions; and
- designing good experimental designs.
A second major component of this subject covers statistical analysis in some detail:
- hypotheses testing and statistical estimation;
- choosing a statistical test and/or model;
- power and sample size calculations as well as dealing with data;
- effective data management;
- analysis;
- presenting skills when using appropriate statistical software; and
- where and when to get statistical advice.
The subject also introduces meta-analysis and highlights the guidelines for quality experimental neuroscience research.
In-class discussions form an integral part of this subject and special emphasis is placed on the application of concepts taught to the student's individual research project through a multi-disciplinary group exercise. This culminates in class presentations at the end of the week; discussions concerning these presentations illustrate various types of study designs and analyses used for different types of research approaches (eg behavioural, molecular, cellular, imaging and clinical).
Intended learning outcomes
On completion of this subject students will be able to:
- Develop an overall understanding at basic to intermediate level of the main principles of good study design and analysis in basic and clinical neurosciences.
- Acquire basic to intermediate level competency in applying ‘building blocks’ of experimental design and analysis to a chosen research problem.
- Appreciate the ultimate importance of quality experimental design and analysis for the overall quality on neuroscience research.
- Become aware of the common pitfall areas where professional statistical expertise is required.
- Gain an awareness of different approaches to experimental study design as applied to different types of neurosciences’ research projects.
- Demonstrate the application of the principles learned in the subject to their research project.
Generic skills
On completion of this subject, students will have developed the following generic skills:
- Research project design and analysis skills.
- Competency in applying experimental design and statistical analysis principles to a variety of research questions and approaches.
- Critical analysis capacity of different research areas in a multi-disciplinary field.
- Awareness of the value of quality research and the wide-ranging consequences of biased research.
- Advanced skills in formulating ideas clearly through oral, written and interpersonal communication.
- The capacity to work in teams and collaborate with other disciplines in the area of neurosciences.
- The capacity to apply concepts learned in their own area of research.
Last updated: 3 November 2022