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Rsch Sch of Finance, Actuarial Studies & App Stats · ANU College of Business and Economics
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.
Typical assessment may include, but is not restricted to: exams, assignments, quizzes, presentations and other assessment as appropriate
Learning outcomes 1, 2, 3, 4, 5, 6, 7
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.
Information about the prescribed textbook will be available via the Class Summary.