Courses & Units
Statistical Analysis Using R KMA711
You are expected to have access to a laptop with sufficient system requirements. It is recommended that you have a recent version of the R programming language (https://www.r-project.org) and RStudio (https://rstudio.com) installed before the unit begins.
Introduction
Statistics is the science of decision making and forms a key foundation of scientific research. This unit will present to postgraduate students, that are early in their research studies, a broad range of applied quantitative data analysis techniques. Students will learn aspects of collecting, processing, analysing, and presenting, quantitative information. Topics include: experimental design, data exploration and presentation, fitting linear models and their extensions (e.g., generalised linear modelling, and mixed effects modelling), model selection, Bayesian methods, and model inference. Students will gain hands-on experience conducting statistical analyses using the R programming language within the RStudio environment, including the use of R Markdown for promoting reproducible research. Examples will be drawn from the biological, physical and social sciences. Students will benefit by having taken an introductory statistics unit as part of an earlier degree.
Summary
| Unit name | Statistical Analysis Using R |
|---|---|
| Unit code | KMA711 |
| Credit points | 12.5 |
| College/School | College of Sciences and Engineering School of Natural Sciences |
| Discipline | Mathematics |
| Coordinator | Doctor Shane Richards |
| Delivered By | University of Tasmania |
| Level | Postgraduate |
Availability
| Location | Study period | Attendance options | Available to | ||
|---|---|---|---|---|---|
| Hobart | Intensive Session Jun | On-Campus | International | Domestic | |
Key
- On-campus
- Off-Campus
- International students
- Domestic students
Note
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Units are offered in attending mode unless otherwise indicated (that is attendance is required at the campus identified). A unit identified as offered by distance, that is there is no requirement for attendance, is identified with a nominal enrolment campus. A unit offered to both attending students and by distance from the same campus is identified as having both modes of study.
Key Dates
| Study Period | Start date | Census date | WW date | End date |
|---|---|---|---|---|
| Intensive Session Jun | 26/6/2023 | 30/6/2023 | 6/7/2023 | 16/7/2023 |
* The Final WW Date is the final date from which you can withdraw from the unit without academic penalty, however you will still incur a financial liability (refer to How do I withdraw from a unit? for more information).
Unit census dates currently displaying for 2023 are indicative and subject to change. Finalised census dates for 2023 will be available from the 1st October 2022. Note census date cutoff is 11.59pm AEST (AEDT during October to March).
Learning Outcomes
- Determine appropriate statistical analyses given the data at hand and the research question posed.
- Conduct statistical analyses using the computer software R, RStudio, and R markdown.
- Assess the validity of the statistical analyses using graphical and advanced techniques.
- Interpret and present statistical results in a written format appropriate for a scientific publication.
| Field of Education | Commencing Student Contribution 1,3 | Grandfathered Student Contribution 1,3 | Approved Pathway Course Student Contribution 2,3 | Domestic Full Fee 4 |
|---|---|---|---|---|
| 010103 | $515.00 | $515.00 | not applicable | $2,522.00 |
1 Please refer to more information on student contribution amounts.
2 Please refer to more information on eligibility and Approved Pathway courses.
3 Please refer to more information on eligibility for HECS-HELP.
4 Please refer to more information on eligibility for FEE-HELP.
If you have any questions in relation to the fees, please contact UConnect or more information is available on StudyAssist.
Please note: international students should refer to What is an indicative Fee? to get an indicative course cost.
Requisites
Mutual Exclusions
You cannot enrol in this unit as well as the following:
KMA353Teaching
| Teaching Pattern | 2 week x Monday, Tuesday, Thursday, and Friday lectorial sessions |
|---|---|
| Assessment | Report (40%)|Portfolio (60%) |
| Timetable | View the lecture timetable | View the full unit timetable |
Textbooks
| Required |
Required readings will be listed in the unit outline prior to the start of classes. |
Links | Booktopia textbook finder |
|---|
The University reserves the right to amend or remove courses and unit availabilities, as appropriate.