Data Analysis in Science (1809.8)
|Available teaching periods||Delivery mode||Location|
|View teaching periods|| On-Campus
|| UC - Canberra, Bruce
|0.125||3||Faculty Of Science And Technology|
|Discipline||Study level||HECS Bands|
|Academic Program Area - Science||Level 1 - Undergraduate Introductory Unit|| Band 1 2021 (Commenced After 1 Jan 2021)
Band 1 2021 (Commenced Before 1 Jan 2021)
Band 2 2013-2020 (Expires 31 Dec 2020)
Learning outcomesOn successful completion of this unit, students will be able to:
1. Recognise essential elements of their research system and understand particular principles of simple system analysis;
2. Design and conduct an experiment within a quality control and assurance framework;
3. Collect and manipulate data that are both of a numerical and non-numerical character;
4. Comprehend, apply and interpret the results of standard data analysis and statistical methods including descriptive statistics, parametric and non-parametric hypothesis testing, linear regression, and simple analyses of variance and be able to express these effectively in a written environment;
5. Use standard statistical packages such as SPSS as well as Excel to prepare, manipulate and process data; and
6. Integrate quantitative information with statistical outcomes towards developing an understanding of a research topic.
Graduate attributes1. UC graduates are professional - employ up-to-date and relevant knowledge and skills
1. UC graduates are professional - use creativity, critical thinking, analysis and research skills to solve theoretical and real-world problems
2. UC graduates are global citizens - think globally about issues in their profession
2. UC graduates are global citizens - make creative use of technology in their learning and professional lives
3. UC graduates are lifelong learners - evaluate and adopt new technology
3. UC graduates are lifelong learners - reflect on their own practice, updating and adapting their knowledge and skills for continual professional and academic development
|Year||Location||Teaching period||Teaching start date||Delivery mode||Unit convener|
|2021||UC - Canberra, Bruce||Semester 2||02 August 2021||On-Campus||Dr Adrian Dusting|
|2022||UC - Canberra, Bruce||Semester 2||01 August 2022||On-Campus||Dr Adrian Dusting|
Recommended (not required): Field, A.P., Miles, J. and Field, Z. (2012) Discovering statistics using R, 1st ed. Sage, ISBN-13: 978-1446200469.
Note that e-text versions of this book are available for purchase, which may present a considerable financial saving. Some copies are available through the UC library.
For students intending to take 10222 Biostatistics in a future semester, it is recommended that you purchase the above textbook. This text supports the content covered in both 1809 Data Analysis in Science and 10222 Biostatistics.
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 mark of 40% or higher on the end of semester assessment; and
- Achieve a final aggregate mark of 50% or higher.
The unit convener reserves the right to question students orally on any of their submitted work.
Supplementary assessment will usually only be offered to students who have failed a single unit in their final semester with a final mark between 45-49% and the unit is required for course completion.
Use of text matching software
Your total mark is calculated as a weighted average of your mark for each assessment item according to the weightings given above. If your total mark is more than 50%, but you do not get the required 40% in the end of semester assessment, you will get a grade of NX.
Otherwise, grades are calculated from your total mark using the university's standard grading schema:
|Pass (P)||50 - 64|
|Credit (CR)||65 - 74|
|Distinction (DI)||75 - 84|
|High Distinction (HD)||85 - 100|
The contact hours for each student in this unit consist of 24 hours of lectures (2 hrs x 12 weeks) and 22 hours of computer laboratories (2 hrs x 11 weeks). The remaining 104 hours of workload should be distributed across self-directed study and the various assessment tasks.
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 two-hour tutorial/computer lab each week (either virtual or face to face) and that you either attend the virtual lectures or listen to the recordings. Although lectures are recorded, we cannot guarantee that the recording will accurately convey all the information presented in the live virtual lecture. Problems with the recordings will not be accepted as an excuse for anything.
As per the University's policy students are expected to be available for all assessment items held during the semester, including the examination period.
Required IT skills
This unit involves online meetings in real time using the Virtual Room in you Canvas teaching site. The Virtual Room allows you to communicate in real time with your lecturer and other students. To participate verbally, rather than just typing, you will need a microphone. For best audio quality we recommend a microphone and speaker headset. For more information and to test your computer, go to the Virtual Room in your UCLearn (Canvas) site and 'Join Course Room'. This will trigger a tutorial to help familiarise you with the functionality of the virtual room.
All students are assumed to be able to:
- Read and print documents on the unit website – mostly in Adobe PDF format
- For the End of Semester Assessment students need to now how to open and run R, R studio and Excel to analyse data (this is covered in lectures and computer labs)
Communicate using email
Use their own scientific (nonprogrammable)
None. Required software is either open source (R, R Studio) or made available by UC for free to UC Students (e.g. Excel, Canvas, Blackboard Collaborate Ultra). Campus computer labs can be used if a student cannot otherwise access computer hardware.
Work placement, internships or practicums
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 Universitty 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 firstname.lastname@example.org if they have any issues accessing their university email account.
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.
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