Data Analysis Skills for Science (11723.1)
Available teaching periods | Delivery mode | Location |
---|---|---|
View teaching periods | On-campus |
Bruce, Canberra |
EFTSL | Credit points | Faculty |
0.125 | 3 | Faculty Of Science And Technology |
Discipline | Study level | HECS Bands |
Academic Program Area - Science | Level 1 - Undergraduate Introductory Unit | Band 2 2021 (Commenced After 1 Jan 2021) Band 3 2021 (Commenced Before 1 Jan 2021) |
Learning outcomes
On successful completion of this unit, students will be able to:1. Apply scientific literacy and numeracy in the search for, collation of, and analysis of evidence;
2. Comprehend, apply and interpret the results of foundational data analysis and statistical methods;
3. Interpret and express analytical findings effectively in written format; and
4. Recognise situations where analytical methods and tools may be applied to chemistry, biology, physics and health.
Graduate attributes
1. ºÚÁϳԹÏÍø graduates are professional - communicate effectively1. ºÚÁϳԹÏÍø graduates are professional - employ up-to-date and relevant knowledge and skills
1. ºÚÁϳԹÏÍø graduates are professional - use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems
Prerequisites
None.Corequisites
None.Incompatible units
None.Equivalent units
1809 Data Analysis in ScienceAssumed knowledge
None.Year | Location | Teaching period | Teaching start date | Delivery mode | Unit convener |
---|---|---|---|---|---|
2024 | Bruce, Canberra | Semester 1 | 05 February 2024 | On-campus | Dr Adrian Dusting |
2024 | Bruce, Canberra | Semester 2 | 29 July 2024 | On-campus | Dr Adrian Dusting |
2025 | Bruce, Canberra | Semester 1 | 03 February 2025 | On-campus | Dr David Hartley |
2025 | Bruce, Canberra | Semester 2 | 28 July 2025 | On-campus | Dr Adrian Dusting |
Required texts
Suggested (not required): Lepš, J. and Šmilauer, P. (2020) Biostatistics with R: an introductory guide for field biologists. Cambridge University Press, ISBN-13: 978-1108480383.
There are a wealth of open access resources available relating to introductory data analysis, R and R Studio, and Microsoft Excel. These will adequately complement the unit's learning materials. For students intending to take further studies in data analysis or data science (using R), it is likely to be worthwhile obtaining the above text.
Submission of assessment items
Special assessment requirements
The final mark for this unit will be calculated by an accumulation of marks from each assessment item. To achieve a passing grade or higher in this subject, students must:
- attempt all assessment items and
- achieve a final aggregate mark of 50% or higher.
The unit convener reserves the right to question students on any of their submitted work for moderation and academic integrity purposes, which may result in an adjustment to the marks awarded for a specific task.
Students must apply academic integrity in their learning and research activities at ºÚÁϳԹÏÍø. This includes submitting authentic and original work for assessments and properly acknowledging any sources used.
Academic integrity involves the ethical, honest and responsible use, creation and sharing of information. It is critical to the quality of higher education. Our academic integrity values are honesty, trust, fairness, respect, responsibility and courage.
ºÚÁϳԹÏÍø students have to complete the annually to learn about academic integrity and to understand the consequences of academic integrity breaches (or academic misconduct).
ºÚÁϳԹÏÍø uses various strategies and systems, including detection software, to identify potential breaches of academic integrity. Suspected breaches may be investigated, and action can be taken when misconduct is found to have occurred.
Information is provided in the Academic Integrity Policy, Academic Integrity Procedure, and University of Canberra (Student Conduct) Rules 2023. For further advice, visit Study Skills.
Learner engagement
The contact hours for each student in this unit consist of 12 hours of lectures (1 hr x 12 weeks) and 24 hours of computer labs (2 hr x 12 weeks). There are an additional up to 12 hours of online content videos. The remaining 102 hours of workload should be distributed across self-directed study and the various assessment tasks.
Participation requirements
It is highly recommended that you attend and participate in all classes. Your participation in both class and online activities will enhance your understanding of the unit content and therefore the quality of your assessment responses. Lack of participation may result in your inability to satisfactorily pass assessment items.
It is expected that you will attend a two-hour computer lab each week and that you either attend the lectures or participate in the live stream. Computer labs will not be recorded. Although lectures are recorded, we cannot guarantee that the recording will accurately convey all the information presented in the live lecture. Problems with the recordings will not be accepted as an excuse for any assessment-related purpose.
Required IT skills
All students are assumed to be able to:
- For the End of Semester Assessment students need to know how to open and run R, R Studio and Excel. Students also need to unzip files to access datasets. These skills are covered in lectures and computer labs.
- Communicate using email
In-unit costs
None. Required software is either open source (R, R Studio) or made available by ºÚÁϳԹÏÍø for free to ºÚÁϳԹÏÍø Students (e.g. Excel, Canvas). Campus computer labs can be used if a student cannot otherwise access computer hardware.
Work placement, internships or practicums
None.
Additional information
Provision of information to the group
Notifications through the Canvas Announcements Forum or the Canvas Discussion Forum are deemed to be made to the whole class. It is the responsibility of the student to ensure that they check for announcements on the Unit's Canvas website (forum messages are also emailed to student email addresses only). Students should ensure they check their student email regularly. The Canvas discussion forum will be checked by staff regularly.
Use of student email account
The University email policy states that "students wishing to contact the University via email regarding administrative or academic matters need to send the email from the University account for identity verification purposes". Therefore all unit enquiries should be emailed using a student university email account. Students should contact servicedesk@canberra.edu.au if they have any issues accessing their university email account.
Caveat
Unforeseen circumstances beyond the unit convener's control could result in changes to the mode of delivery of lectures, tutorials and practicals (where applicable) and assessments. Students will be advised if this occurs and appropriate alternatives will be arranged.
- Semester 2, 2024, On-campus, ºÚÁϳԹÏÍø - Canberra, Bruce (219501)
- Semester 1, 2024, On-campus, ºÚÁϳԹÏÍø - Canberra, Bruce (217150)
- Semester 2, 2023, On-campus, ºÚÁϳԹÏÍø - Canberra, Bruce (214956)
- Semester 1, 2023, On-campus, ºÚÁϳԹÏÍø - Canberra, Bruce (213321)
- Semester 2, 2022, On-campus, ºÚÁϳԹÏÍø - Canberra, Bruce (209097)