SIT741 - Statistical Data Analysis
| Year: | 2023 unit information |
|---|---|
| Enrolment modes: | Trimester 2: Burwood (Melbourne), Cloud (online) |
| Credit point(s): | 1 |
| EFTSL value: | 0.125 |
| Prerequisite: | Nil |
| Corequisite: | SIT718 For students enrolled in S577: 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. |
| Scheduled learning activities - campus | 1 x 2 hour online class per week, 1 x 2 hour workshop per week. weekly drop-in sessions. |
| Scheduled learning activities - cloud (online) | Online independent and collaborative learning including optional scheduled activities as detailed in the unit site. |
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.
Unit Fee Information
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