« Business and Economics

Mon 08 Nov 2021 - Fri 17 Dec 2021

10:00AM

3 Sessions

Face-to-face

Priya Dev

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 representation of information.

Topics 

  1. Introduction to the R statistical computing environment
  2. Graphics environments and interactive graphics
  3. Constructing graphics in R
  4. Principles of graphic construction including examples of good and bad graphics
  5. Constructing graphical representations for one dimensional data

Learning outcomes 

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

  1. Demonstrate basic knowledge of the R statistical computing language, particularly graphical capabilities
  2. Explain and be able to apply the principles of good data representation
  3. Explain and be able to use various graphics environments, interactive graphics and graphical objects
  4. 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.

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