SLE452 - Research Design and Data Analysis
Unit details
| Year: | 2022 unit information |
|---|---|
| Important Update: | Unit delivery will be in line with the most current COVIDSafe health guidelines. We continue to tailor learning experiences for each unit to achieve the best possible mix of online and on-campus activities that successfully blend our approaches to learning, working and research. Please check your unit sites for announcements and updates. Last updated: 4 March 2022 |
| Enrolment modes: | Semester 1: Cloud (online) |
| Credit point(s): | 1 |
| EFTSL value: | 0.125 |
| Unit Chair: | Semester 1: Matthew Symonds Semester 2: Anthony Rendall |
| Cohort rule: | (This unit is restricted to students enrolled in S400, S401, S494) |
| Prerequisite: | Nil |
| Corequisite: | Nil |
| Incompatible with: | Nil |
| Typical study commitment: | Students will on average spend 150 hours over the teaching period undertaking the teaching, learning and assessment activities for this unit. |
| Scheduled learning activities - cloud: | Online independent and collaborative learning including optional scheduled activities as detailed in the unit site. |
Content
Research design and data analysis is an essential part of scientific and industry research but many graduates in life and environmental sciences have only limited experience of applying it in this context. SLE452 aims to help research students develop the skills to design, implement and analyse quantitative outcomes from a research project across a broad range of settings. This unit will build on basic statistical knowledge from other units completed in their undergraduate degree. Students will learn how to design sophisticated sampling and experimental programs that maximise interpretability and efficiency, and with a focus on modern statistical models, understand the logic and assumptions underlying statistical analyses as applied in biological research, develop the practical ability to analyse data and interpret and present the results using modern software, and learn how to critically evaluate the data analyses used in the published literature.
| ULO | These are the Learning Outcomes (ULO) for this unit. At the completion of this unit, successful students can: | Deakin Graduate Learning Outcomes |
|---|---|---|
| ULO1 | Learn how to design sampling and experimental programs for theoretical and applied research questions across the spectrum of biological sciences. | GLO1: Discipline-specific knowledge and capabilities |
| ULO2 | Understand the logic and assumptions underlying common statistical models as applied in biological research. | GLO1: Discipline-specific knowledge and capabilities |
| ULO3 | Develop the practical ability to analyse data and interpret and present the results using modern software. | GLO1: Discipline-specific knowledge and capabilities |
| ULO4 | Learn how to critically evaluate the design and data analyses used in the published literature. | GLO1: Discipline-specific knowledge and capabilities |
These Unit Learning Outcomes are applicable for all teaching periods throughout the year
Assessment
| Assessment Description | Student output | Grading and weighting (% total mark for unit) | Indicative due week |
|---|---|---|---|
| Research design quiz | 30-minute online quiz | 20% | Week 5 |
| Critical evaluation | Written report, 1,000-word maximum | 30% | Week 7 |
| Biostatistics test | 2-hour open book test | 50% | Week 9 |
The assessment due weeks provided may change. The Unit Chair will clarify the exact assessment requirements, including the due date, at the start of the teaching period.
Learning Resource
There is no prescribed text. Unit materials are provided via the unit site. This includes unit topic readings and references to further information.
Unit Fee Information
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