Hobart: semester 1 and 2, blended delivery
Distance: semester 1
Launceston: semester 1 and 2 blended delivery
Cradle Coast: semester 1 blended delivery
Data Handling and Statistics 1 is the first of three applied statistics units offered by the School of Natural Sciences (Mathematics). Statistics is the science of decision making, and as such forms a key foundation of any scientific research. This unit develops skills in statistical analysis and project design.
Data Handling and Statistics 1 is an applied unit that develops conceptual understanding of the foundations of modern Statistics together with practical skills in data analysis. This is a hands-on unit that provides experience with the common techniques of descriptive and inferential statistics.
|Unit name||Data Handling and Statistics 1|
|College/School||College of Sciences and Engineering
School of Natural Sciences
|Coordinator||Doctor Danijela Ivkovic|
|Available as an elective?||Yes|
|Delivered By||University of Tasmania|
|Location||Study period||Attendance options||Available to|
|Cradle Coast||Semester 1||On-Campus||International||Domestic|
- International students
- Domestic students
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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.
|Study Period||Start date||Census date||WW date||End date|
* 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).
- summarize and explore large data sets using appropriate numeric and graphical tools in order to communicate statistical concepts to both scientific and lay audiences.
- recognize the key issues involved in designing a survey or experiment, and assess strengths and weaknesses in statistical arguments.
- identify and apply appropriate statistical techniques to make inferences based on data.
- perform common statistical analyses in a statistical computing package.
|Field of Education||Commencing Student Contribution 1||Grandfathered Student Contribution 1||Approved Pathway Course Student Contribution 2||Domestic Full Fee|
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.
Please note: international students should refer to What is an indicative Fee? to get an indicative course cost.
You cannot enrol in this unit as well as the following:KMA553
Blended delivery: 1-hr video lectures, 1-hr tutorial, 1-hr computer lab, 1-hr face-to--face weekly.
|Assessment||Quiz (20%)|Examination (40%)|Project 1: Descriptive Statistics (15%)|Project 2: Design task (10%)|Report (15%)|
|Timetable||View the lecture timetable | View the full unit timetable|
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.