SIT741 - Statistical Data Analysis
| Year: | 2024 unit information |
|---|---|
| Enrolment modes: | Trimester 2: Burwood (Melbourne), Online |
| Credit point(s): | 1 |
| EFTSL value: | 0.125 |
| Prerequisite: | Nil |
| Corequisite: | Nil |
| Incompatible with: | Nil |
| Study commitment | Students will on average spend 150 hours over the teaching period undertaking the teaching, learning and assessment activities for this unit. This will include educator guided online learning activities within the unit site. |
| Scheduled learning activities - campus | 1 x 3 hour seminar per week, weekly meetings. |
| Scheduled learning activities - online | Online independent and collaborative learning including 1 x 2 hour online seminar per week, weekly meetings. |
Content
The aim of this unit is to provide students with the opportunity to develop advanced working knowledge in statistical modelling and statistical programming. Students will learn how to apply advanced statistical theories such as generalised additive modelling to model real-world data problems. They will also learn about advanced statistical programming using the R language, to perform simulation, model development, model checking, and result interpretation.
Upon successful completion of this unit, students will be able to apply the right statistical models, including generalised linear models and generalised additive models, to solve problems of real-world complexity. They will know how to use R to transform untidy data to tidy data, to perform exploratory data analysis, to develop and check models, and to communicate the analysis results.
Hurdle requirement
To be eligible to obtain a pass in this unit, students must meet certain milestones as part of the portfolio.
Unit Fee Information
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