Students required to check the timetable for commencement date of this unit.
Please note results for this unit will not be available in time for August graduations.
This unit is an introduction to quantitative data analysis techniques. Covering topics from basic inference through to generalised linear models, time series analysis and clustering and discrimination, this subject gives students the opportunity to become familiar with a variety of modern statistical techniques and their implementation using the R programming language. Students will improve their ability to recognise good experimental design, choose appropriate analysis techniques, present their statistical analyses, and learn the importance of meeting statistical assumptions when analysing data. The theoretical skills above will be reinforced using a combination of short exercises that contribute to a portfolio assignment, and a larger practical assignment that may involve the student’s own data, if available.
|Unit name||Statistical Analysis Using R|
|Faculty/School||College of Sciences and Engineering
School of Natural Sciences
|Discipline||Mathematics & Physics|
Dr Shane A. Richards
A/Prof B Holland, A/Prof M Charleston, Mr D Palmer
|Available as student elective?||Yes|
|Location||Study period||Attendance options||Available to|
|Hobart||Intensive Session Jun||On-Campus||International||Domestic|
- International students
- Domestic students
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|Study Period||Start date||Census date||WW date||End date|
|Intensive Session Jun||24/6/2019||28/6/2019||4/7/2019||14/7/2019|
* 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 (see withdrawal dates explained for more information).
Unit census dates currently displaying for 2019 are indicative and subject to change. Finalised census dates for 2019 will be available from the 1st October 2018.
|Band||CSP Student Contribution||Full Fee Paying (domestic)||Field of Education|
|2||2019: $1,169.00||2019: $2,321.00||010103|
Fees for next year will be published in October. The fees above only apply for the year shown.
Please note: international students should refer to this page to get an indicative course cost.
Students must be enrolled in a PhD, Masters or Honours
On-campus component - 8 days (over 3 weeks) 2-3hr lecture & 2-3hr practical, self study before and after on-campus sessions.
2-3 assignments worth 100%
|Timetable||View the lecture timetable | View the full unit timetable|
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