• Offered by Rsch Sch of Finance, Actuarial Studies & App Stats
  • ANU College ANU College of Business and Economics
  • Classification Transitional
  • Course subject Statistics
  • Areas of interest Statistics

This course introduces the principles of data representation, summarisation and presentation with particular emphasis on the use of graphics. The course will use the R Language in a modern computing environment. Topics to be discussed include:

·        Data representation; examples of good and bad graphics; principles of graphic construction; some pitfalls to be avoided; presentation graphics.

·        Graphics environments; interactive graphics; windows; linked windows; graphics objects.

·        Statistical graphics; stem and leaf plots, box plots, histograms; smoothing histograms; quantile-quantile plots; representing multivariate data; scatterplots; clustering; stars and faces; dynamic graphics including data rotation and brushing.

·        Relationships between variables; smoothing scatterplots; simple regression; modelling and diagnostic plots; exploring surfaces; contour plots and perspective plots; multiple regression; relationships in time and space; time series modelling and diagnostic plots.

Learning Outcomes

Upon successful completion, students will have the knowledge and skills to:

  1. Demonstrate detailed knowledge of the R statistical computing language, particularly graphical capabilities;
  2. Explain in detail and be able to apply the principles of good data representation;
  3. Explain in detail and be able to use various graphics environments, interactive graphics and graphics objects;
  4. Construct graphical representations of one dimensional data;
  5. Construct graphical representations for multivariate data including scatterplots, and dynamic graphics;
  6. Use diagnostic plots when conducting statistical modelling to explore and refine statistical models for data, including detailed explanations of such use; and
  7. Construct and interpret graphical displays for dependent data.

Other Information

Offerings of this course outside of Semester 1 and Semester 2 are available only to students enrolled in Master of Applied Data Analytics.

Indicative Assessment

  1. Typical assessment may include, but is not restricted to: exams, assignments, quizzes, presentations and other assessment as appropriate (100) [LO 1,2,3,4,5,6,7]

The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.

Workload

Students are expected to commit 130 hours of work in completing this course. This includes time spent in scheduled classes and self-directed study time.

Inherent Requirements

Not applicable

Requisite and Incompatibility

To enrol in this course you must have completed STAT7055 or STAT6039 or STAT6013 or be enrolled in the Master of Statistics. Incompatible with STAT4026 and STAT3011.

Prescribed Texts

Information about the prescribed textbook will be available via the Class Summary.

Specialisations

Fees

Tuition fees are for the academic year indicated at the top of the page.  

If you are a domestic graduate coursework or international student you will be required to pay tuition fees. Tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.

Student Contribution Band:
2
Unit value:
6 units

If you are an undergraduate student and have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). You can find your student contribution amount for each course at Fees.  Where there is a unit range displayed for this course, not all unit options below may be available.

Units EFTSL
6.00 0.12500
Note: Please note that fee information is for current year only.

Offerings, Dates and Class Summary Links

The list of offerings for future years is indicative only.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.

Second Semester

Class number Class start date Last day to enrol Census date Class end date Mode Of Delivery Class Summary
7340 27 Jul 2020 03 Aug 2020 31 Aug 2020 30 Oct 2020 In Person N/A

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