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◄Faculty of Business and Economics►

AA037014 STATISTICAL COMPUTING
3 Credits

Learning Outcomes At the end of the course, students are able to:
(1) Develop statistical function codes in R;
(2) apply the functionality of R by using add-on packages;
(3) evaluate modeling assumptions using simulation; and
(4) integrate the prose, codes and results for
communication.

Synopsis of Course Computational data analysis is an essential part of modern
Contents statistics. This experiential work-based learning course
employs computational, graphical, and numerical approaches
to solve statistical problems. The course focuses on an open
source software statistical language as an ideal computing
environment. The goal of this course is to introduce students
to the R programming environment and related eco-system
and thus provide them with an in-demand skill-set, in both the
research and business environments. This course provides
guidance to students through the steps of importing,
wrangling, exploring, and modeling the data, and
communicating the results. This course prepares students to
take up analytic and data science courses in the future. No
previous programming experience is assumed.

Assessment Weightage Continuous Assessment: 60%
Final Examination: 40%

Medium of Instruction English

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