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 ( and RStudio ( installed before the unit begins.


Statistics is the science of decision making and forms a key foundation of scientific research. This unit will introduce students to a broad range of 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, and 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.


Unit name Statistical Analysis Using R
Unit code KMA711
Credit points 12.5
Faculty/School College of Sciences and Engineering
School of Natural Sciences
Discipline Mathematics

Shane Richards

Teaching staff

Barbara Holland, Michael Charleston

Level Postgraduate
Available as student elective? Yes
Breadth Unit? No


Location Study period Attendance options Available to
Hobart Intensive Session Jun On-Campus International Domestic


International students
Domestic students

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Key Dates

Study Period Start date Census date WW date End date
Intensive Session Jun 28/6/2021 2/7/2021 8/7/2021 18/7/2021

* 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).

About Census Dates


Field of Education Commencing Student Contribution 1 Grandfathered Student Contribution 1 Approved Pathway Course Student Contribution 2 Domestic Full Fee
010103 $493.00 $493.00 not applicable $2,402.00

1 Please refer here more information on student contribution amounts.
2 Information on eligibility and Approved Pathway courses can be found here
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 this page to get an indicative course cost.


Students must be enrolled in a PhD, Masters or Honours


Mutual Exclusions

You cannot enrol in this unit as well as the following:



Teaching Pattern

On-campus component - 8 days (over 3 weeks) 2-3hr lecture & 2-3hr practical, self study before and after on-campus sessions.


2 assignments worth 100%: portfolio exercises (60%), project report (40%)

TimetableView the lecture timetable | View the full unit timetable




Fränzi Korner-Nievergelt, Tobias Roth, Stefanie von Felten, Jérôme Guélat, Bettina Almasi, and Pius Korner-Nievergelt (2015) Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan. Academic Press.

Claus Thorn Ekstrom (2017) The R primer. Second edition. CRC Press.

LinksBooktopia textbook finder

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