| Effective Term: | 2026/05 |
| Institute / School : | Institute of Innovation, Science & Sustainability |
| Unit Title: | Statistics for Prediction |
| Unit ID: | STATS2101 |
| Credit Points: | 15.00 |
| Prerequisite(s): | (STATS1000) |
| Co-requisite(s): | Nil |
| Exclusion(s): | Nil |
| ASCED: | 010103 |
| Other Change: | |
| Brief description of the Unit |
This unit introduces the two main themes of predictive statistical analysis - regression and time series methods. Data from various disciplinary contexts is utilised, and there is a strong emphasis on computing skills, 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 | | | | | | |
|
| Learning Outcomes: |
| Knowledge: |
| K1. | Describe relationship between dependent and independent variables using appropriate linear regression models. |
|
| K2. | List regression assumptions, and evaluate model appropriateness from these assumptions. |
|
| K3. | Recognise importance of regression models for predictions. |
|
| Skills: |
| S1. | Apply statistical software to develop regression models. |
|
| S2. | Build regression models using different methods and apply appropriate diagnostics for detecting outlying and influential observations. |
|
| S3. | Perform appropriate hypothesis tests to determine the significance of independent variables in a regression model. |
|
| S4. | Build appropriate time series regression models. |
|
| S5. | Present clear, orderly and informative statistical summaries and technical reports. |
|
| Application of knowledge and skills: |
| A1. | Build regression models for real life applications. |
|
| A2. | Apply regression models to predict future events and conditions. |
|
| Unit Content: |
•Simple and multiple regression: model selection and evaluation, transformations, residuals and influence.
•Time series analysis and forecasting: classical decomposition, exponential smoothing, regression methods, sinusoidal models. |
| Graduate Attributes: |
| Federation University recognises that students require key transferable employability skills to prepare them for their future workplace and society. FEDTASKS (Transferable Attributes Skills and Knowledge) provide a targeted focus on five key transferable Attributes, Skills, and Knowledge that are be embedded within curriculum, developed gradually towards successful measures and interlinked with cross-discipline and Co-operative Learning opportunities. One or more FEDTASK, transferable Attributes, Skills or Knowledge must be evident in the specified learning outcomes and assessment for each FedUni Unit, and all must be directly assessed in each Course.
|
| FED TASK and descriptor | Development and acquisition of FEDTASKS in the Unit | | Level | FEDTASK 1
Interpersonal | Students will demonstrate the ability to effectively communicate, inter-act and work with others both individually and in groups. Students will be required to display skills in-person and/or online in: • Using effective verbal and non-verbal communication • Listening for meaning and influencing via active listening • Showing empathy for others • Negotiating and demonstrating conflict resolution skills • Working respectfully in cross-cultural and diverse teams. | Level 1 - Students require directions and boundaries from mentor | FEDTASK 2
Leadership | Students will demonstrate the ability to apply professional skills and behaviours in leading others. Students will be required to display skills in: • Creating a collegial environment • Showing self -awareness and the ability to self-reflect • Inspiring and convincing others • Making informed decisions • Displaying initiative | Level 2 - Student demonstrates some independence within provided guidelines | FEDTASK 3
Critical Thinking and Creativity | Students will demonstrate an ability to work in complexity and ambiguity using the imagination to create new ideas. Students will be required to display skills in: • Reflecting critically • Evaluating ideas, concepts and information • Considering alternative perspectives to refine ideas • Challenging conventional thinking to clarify concepts • Forming creative solutions in problem solving. | Level 1 - Students require directions and boundaries from mentor | FEDTASK 4
Digital Literacy | Students will demonstrate the ability to work fluently across a range of tools, platforms and applications to achieve a range of tasks. Students will be required to display skills in: • Finding, evaluating, managing, curating, organising and sharing digital information • Collating, managing, accessing and using digital data securely • Receiving and responding to messages in a range of digital media • Contributing actively to digital teams and working groups • Participating in and benefiting from digital learning opportunities. | Level 1 - Students require directions and boundaries from mentor | FEDTASK 5
Sustainable and Ethical Mindset | Students will demonstrate the ability to consider and assess the consequences and impact of ideas and actions in enacting ethical and sustainable decisions. Students will be required to display skills in: • Making informed judgments that consider the impact of devising solutions in global economic environmental and societal contexts • Committing to social responsibility as a professional and a citizen • Evaluating ethical, socially responsible and/or sustainable challenges and generating and articulating responses • Embracing lifelong, life-wide and life-deep learning to be open to diverse others • Implementing required actions to foster sustainability in their professional and personal life. | Level 3 - Student works independently with limited guidance or works within self-determined guidelines appropriate to context |
|
| | Learning Outcomes Assessed | Assessment Tasks | Assessment Type | Weighting | | 1. | K1, K2, K3, S1, S2, S3, S4, S5, A1 | Read research and apply various aspects of regression and time series. | Assignments | 40 - 60% | | 2. | K1, K2, K3, S1, S2, S3, S4, S5, A2 | Summarise theoretical aspects of the unit | Test/Viva | 40 - 60% |
|