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No dates are currently scheduled.

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: In-person lecture and lab 10am-12pm and 1pm-3pm
        Tuesday 30 November: In-person lecture and lab 10am-12pm and 1pm-3pm
        Wednesday 1 December: In-person lecture and lab 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 modelling and relationships.

Topics 

  1. Constructing graphical representations for multivariate data
  2. Construction and use of diagnostics plots when conducting statistical analysis of data
  3. Constructing and interpreting graphical displays for dependent data

Learning outcomes 

Upon successful completion, enrollee's will have the knowledge and skills to:

  1. Demonstrate detailed knowledge of the R statistical computing language, particularly graphical capabilities
  2. Construct graphical representations for multivariate data including scatterplots, and dynamic graphics
  3. Use diagnostic plots when conducting statistical modelling to explore and refine statistical models for data, including detailed explanations of such use
  4. Construct and interpret graphical displays for dependent 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 

Graphical Data Analysis A is the prerequisite for Graphical Data Analysis B.

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 A.

Successful completion of Graphical Data Analysis A and B can lead to specified credit for the course STAT7026 Graphical Data Analysis.

Details 

Course Code: DATA31

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.

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