Courses & Units

Data Handling and Statistics 3 KMA353

Note:

Introduction

Data Handling and Statistics 3 is the third applied statistics units offered by the School of Natural Sciences (Mathematics). This unit is required in the Statistics and Decision Science major and it provides an extension of the concepts, methods and tools introduced in KMA253. It is a 'hands-on' course in which the emphasis is on the development of skills in the selection and application of upper-level statistical methodology. Emphasis is also placed on the presentation of statistical analyses in a written format that promotes reproducible research. Topics covered in the course include: hypothesis testing, experimental design, frequentist and Bayesian inference, analysis presentation, generalised linear modelling; mixed-effects modelling, multinomial regression, and model selection. Expertise with the statistical computing language R and RStudio will be extended, including the application of R Markdown for producing reproducible research. Examples will be drawn from the biological, physical and social sciences.

Summary

Unit name Data Handling and Statistics 3
Unit code KMA353
Credit points 12.5
College/School College of Sciences and Engineering
School of Natural Sciences
Discipline Mathematics
Coordinator Doctor Shane Richards
Available as an elective? Yes
Delivered By University of Tasmania
Level Advanced

Availability

Location Study period Attendance options Available to
Hobart Semester 1 On-Campus International Domestic

Key

On-campus
Off-Campus
International students
Domestic students
Note

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Key Dates

Study Period Start date Census date WW date End date
Semester 1 20/2/2023 21/3/2023 10/4/2023 28/5/2023

* 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).

About Census Dates

Learning Outcomes

  • Describe statistical approaches commonly adopted in the sciences.
  • Apply statistical methods using the R programming language.
  • Evaluate the validity of a statistical analysis.
  • Interpret a statistical analysis in written format
Field of Education Commencing Student Contribution 1 Grandfathered Student Contribution 1 Approved Pathway Course Student Contribution 2 Domestic Full Fee
$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

Prerequisites

KMA253

Teaching

Teaching Pattern

Each week students will engage in 3 x 1-hr face-to-face recorded lectorials, and a 1 x 1-hr face-face computer lab session (not recorded).

AssessmentTests (46%)|Projects (54%)
TimetableView 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.

Recommended

Korner-Nievergelt, F., Roth, T., von Felten, S., Guélat, J., Almasi, B., Korner-Nievergelt, P. (2015) Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan. Academic Press.

LinksBooktopia textbook finder

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