| Effective Term: | 2024/05 |
| Institute / School : | Institute of Innovation, Science & Sustainability |
| Unit Title: | Quantitative Foundations and Numerical Analysis |
| Unit ID: | BUHON4005 |
| Credit Points: | 15.00 |
| Prerequisite(s): | Nil |
| Co-requisite(s): | Nil |
| Exclusion(s): | Nil |
| ASCED: | 080300 |
| Other Change: | |
| Brief description of the Unit |
Students are introduced firstly to data measurement, data models, probability distributions and forms of data presentation. Sampling, sample distributions and statistical inference including hypothesis testing are then described. The unit concludes with descriptions of correlation-based methods including ANOVA, regression and factoring, time series techniques, categorical data analysis and nonparametric statistics. Applied statistical methods or analytical techniques for econometric modelling, structural equation modelling, discriminant analysis, cluster analysis or others may be described according to student research requirements |
| Grade Scheme: | Graded (HD, D, C, P, MF, F, XF) |
| Work Experience Indicator: |
| No work experience |
| Placement Component: | |
| Supplementary Assessment:No |
| Supplementary assessment is not available to students who gain a fail in this Unit. |
| Course Level: |
| Level of Unit in Course | AQF Level(s) of Course | | 5 | 6 | 7 | 8 | 9 | 10 | | Introductory | | | | | | | | Intermediate | | | | | | | | Advanced | | | |  | | |
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| Learning Outcomes: |
| Knowledge: |
| K1. | Describe fundamental concepts in numerical data analysis including data forms, sampling and hypothesis testing |
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| K2. | Explain basis statistical approaches to analysing data to answer various research questions |
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| K3. | Compare and contrast statistical methods with respect to assumptions, limitations and interpretation of results |
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| Skills: |
| S1. | Construct summary models appropriate for the data and research purpose |
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| S2. | Identify numerical sampling techniques for inferential statistical analysis and hypothesis testing |
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| S3. | Determine suitable statistical methods and techniques to answer research questions for a range of data contexts |
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| Application of knowledge and skills: |
| A1. | Report and present data models summarising numerical distributions |
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| A2. | Devise and implement a sampling framework designed to answer a specified research question |
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| A3. | Apply analytical techniques to a data set with results reported in the context of key assumptions, findings, and limitations |
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| Unit Content: |
Basic numerical analysis including probability distributions and suitable forms of data presentation Sampling from populations, statistical inference and hypothesis testing Quantitative methods and techniques including correlational analysis plus advanced techniques |
| Graduate Attributes: |
| | Learning Outcomes Assessed | Assessment Tasks | Assessment Type | Weighting | | 1. | K1, K3, S1, S3 | Self-paced online quiz | Short Answer | 10 - 20% | | 2. | K3, S2, S3, A3 | Quantitative method application and interpretation | Written Report and Coding Files | 40 - 60% | | 3. | K1, K2, S1, S2, A1, A2 | Sampling plan and data analysis | Report and Presentation | 30 - 50% |
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