| Effective Term: | 2027/05 |
| Institute / School : | Institute of Innovation, Science & Sustainability |
| Unit Title: | Statistical Methods |
| Unit ID: | STATS1000 |
| Credit Points: | 15.00 |
| Prerequisite(s): | Nil |
| Co-requisite(s): | Nil |
| Exclusion(s): | Nil |
| ASCED: | 010103 |
| Other Change: | |
| Brief description of the Unit |
This unit introduces students to the full range of descriptive statistical techniques, and also introduces the key concepts underlying statistical inference. A wide range of basic inferential techniques are introduced. Data from various disciplinary contexts is utilised, and there is a strong emphasis on computing skills, statistical decision making, interpretation of computer output and communication of statistical results and conclusions. |
| Grade Scheme: | Graded (HD, D, C, P, MF, F, XF) |
| Work Experience Indicator: |
| No work experience |
| Placement Component: | |
| Supplementary Assessment:Yes |
| Where supplementary assessment is available a student must have failed overall in the Unit but gained a final mark of 45 per cent or above, has completed all major assessment tasks (including all sub-components where a task has multiple parts) as specified in the Unit Description and is not eligible for any other form of supplementary assessment |
| 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: |
| Skills: |
| Application of knowledge and skills: |
| Other outcomes: |
| O1. | Describe and summarise data sets using appropriate statistical measures, probability distributions, and graphical techniques. |
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| O2. | Apply standard statistical software to manage data and perform descriptive and inferential analyses. |
|
| O3. | Choose and justify appropriate inferential techniques to investigate research hypotheses. |
|
| O4. | Interpret hypothesis tests, regression analysis, and analysis of variance and justify conclusions in relation to real world problems. |
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| O5. | Communicate statistical processes and findings clearly using appropriate language. |
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| Unit Content: |
•Data presentation and basic descriptive statistics.
•Discrete and continuous probability distributions.
•Estimation and hypothesis testing (t-tests for single sample, paired and independent).
•Non-parametric alternatives.
•Chi-square tests.
•Correlation and regression.
•Introduction to 1-way and 2-way analysis of variance. |
| Graduate Attributes: |
| | Learning Outcomes Assessed | Assessment Tasks | Assessment Type | Weighting | Professional Standards |
| 1. |
1, 2, 4, 5 |
Practical use of appropriate statistical packages and interpretation of output. |
Computer lab quizzes and tutorial exercises |
10 - 20 % |
|
| 2. |
1, 2, 3, 4, 5 |
Produce appropriate statistical output (including under supervision) to respond to a brief. Critically justify interpretation, decision making and statistical process verbally in response to questioning. |
Data analysis tasks, Oral conversations |
40 - 60 % |
|
| 3. |
3, 4, 5 |
Interpret statistical outputs and justify conclusions in relation to real-world problems. |
Case study |
20 - 40 % |
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