Unit description
Provides a critical evaluation of data analysis techniques and current approaches to best practice evaluation techniques in the applied setting. Describes contemporary alternatives to null hypothesis testing in the context of their value for real-world professional conduct within a scientist-practitioner framework. Supports best practices in data management, programme evaluation and scientific and applied dissemination of outcomes and utilises a combination of problem based learning applied to a project and student reflective practice.
Unit content
- Designing an effective data analysis strategy: Issues and resolutions
- Introduction to the “New” statistics: effect size estimation
- Alternatives to NHT: Bayes and p-rep
- Research in the real world: single case designs
- Research in the real world: time series
- Real world applications: programme evaluation
- Real world applications: Big data
- Good data practices
Learning outcomes
Unit Learning Outcomes express learning achievement in terms of what a student should know, understand and be able to do on completion of a unit. These outcomes are aligned with the graduate attributes. The unit learning outcomes and graduate attributes are also the basis of evaluating prior learning.
Learning outcomes and graduate attributes
| On completion of this unit, students should be able to: | GA1 | GA2 | GA3 | GA4 | GA5 | GA6 | GA7 | |
|---|---|---|---|---|---|---|---|---|
| 1 | explain and defend their strategy for analysis of data from their thesis research or another appropriate project | Knowledge of a discipline | ||||||
| 2 | critically evaluate the use of NHT methods for data analysis and employ alternatives where more appropriate | Knowledge of a discipline | ||||||
| 3 | select and apply appropriate research strategies and techniques for analysis of real-world (small sample) data | Creativity | ||||||
| 4 | be cognisant of the impact of selected data-analytic techniques for solving real-world problems | Creativity | ||||||
| 5 | identify and apply analytic techniques relevant to program evaluation and their importance in practical settings and application | Knowledge of a discipline | ||||||
| 6 | utilise appropriate methods to manage data and to ensure the integrity of data. | Ethical practice | ||||||
Prescribed texts
Session 2
- No prescribed texts.
Teaching and assessment
Coffs Harbour
| Teaching method |
| Lecture on-site 2 hrs |
| Workshop on-site 2 hrs |
| Assessment | |
| Data analysis proposal | 25% |
| Critical review | 75% |
Fee information
Domestic
Commonwealth Supported courses
For information regarding Student Contribution Amounts please visit the Student Contribution Amounts.
Commencing 2015 Commonwealth Supported only. Student contribution band: 2
Fee paying courses
For POSTGRADUATE or UNDERGRADUATE full fee paying courses please check Domestic Postgraduate Fees OR Domestic Undergraduate Fees
International
Please check the international course and fee list to determine the relevant fees.