Details
Session 1: Self-study Period (weeks 1-3)
Students will work through the textbook and practice problems, as well as watch videos.
Session 2: In-person period (week 4)
Monday 29 November: Online sessions 10am-12pm and 1pm-3pm
Tuesday 30 November: Online sessions 10am-12pm and 1pm-3pm
Wednesday 1 December: Online sessions 10am-12pm and 1pm-3pm
Session 3: Self-study period (weeks 5-6)
Students will work through class notes and practice problems, as well as watch videos.
Description
This micro-credential aims to facilitate an understanding of graphical representation of information.
Topics
- Introduction to the R statistical computing environment
- Graphics environments and interactive graphics
- Constructing graphics in R
- Principles of graphic construction including examples of good and bad graphics
- Constructing graphical representations for one dimensional data
Learning outcomes
Upon successful completion, enrollee's will have the knowledge and skills to:
- Demonstrate basic knowledge of the R statistical computing language, particularly graphical capabilities
- Explain and be able to apply the principles of good data representation
- Explain and be able to use various graphics environments, interactive graphics and graphical objects
- Construct graphical representations of one dimensional data
Indicative assessment
Assignment 1: Presentation graphics (20%), 8-page limit, LO: 1 and 2.
Assignment 2: Project analysing a dataset (80%), 8-page limit, LO: 1, 2, 3 and 4.
Assumed knowledge
This micro-credential is taught at graduate level and assumes the generic skills of a Bachelors or equivalent.
Micro-credential stack information
This micro-credential may be undertaken as part of a stack by completing Graphical Data Analysis B.
Successful completion of Graphical Data Analysis A and B can lead to specified credit for the course STAT7026 Graphical Data Analysis.
Details
Course Code: DATA30
Workload: 72 hours
- Contact hours: 12 hours
- Individual study and assessment: 60 hours
ANU unit value: 3 units
Course Code Level: 7000
Contact: Jo Drienko (RSFAS DDE)
This Micro-credential is taught at a graduate level. This is not an AQF qualification.
Related Courses
Escape from Excel: Data Wrangling and Visualisation in the Health and Environmental Sciences using R
This micro-credential includes one full-day session on campus at ANU. Description Producing attractive, informative data visualisations is critical to the effective communication of quantitative ...
View Details / EnrolGraphical Data Analysis B
Details Session 1: Self-study Period (weeks 1-3) Students will work through the textbook and practice problems, as well as watch videos. Session 2: In-person period (week 4) Monday...
View Details / EnrolGraphical Data Analysis B
Details Session 1: Self-study Period (weeks 1-3) Students will work through the textbook and practice problems, as well as watch videos. Session 2: In-person period (week 4) Date T...
View Details / Enrol