SDST3622 Data visualization (6 credits) Academic Year 2025
Offering Department SCDS (Department of Statistics and Actuarial Science) Quota 50
Course Co-ordinator Prof D Y Zhang, SCDS (Department of Statistics and Actuarial Science) < doraz@hku.hk >
Teachers Involved (Prof D Y Zhang,Statistics & Actuarial Science)
Course Objectives This course will focus on how to work with statistical graphics, graphics that display statistical data, to communicate and analyze data. Students will learn a set of tools such as R to create these graphics and critically evaluate them.
Course Contents & Topics Grammar of graphics, visualizing patterns over time, visualizing relationship, visualizing spatial relationships, visualizing texts.
Course Learning Outcomes
On successful completion of this course, students should be able to:

CLO 1 choose the best chart that fits the data
CLO 2 create a compelling visualization using computer software
CLO 3 communicate effectively using statistical graphics
CLO 4 critically evaluate graphics and suggest improvements
Pre-requisites
(and Co-requisites and
Impermissible combinations)		 Pass in SDST2602 or SDST3902
Only for students admitted in 2025 and thereafter.
Course Status with Related Major/Minor /Professional Core 2U000C00 Course not offered under any Major/Minor/Professional core
2024 Bachelor of Arts and Sciences in Applied Artificial Intelligence ( Disciplinary Elective )
2024 Major in Decision Analytics ( Disciplinary Elective )
2023 Bachelor of Arts and Sciences in Applied Artificial Intelligence ( Disciplinary Elective )
2023 Major in Decision Analytics ( Disciplinary Elective )
2022 Bachelor of Arts and Sciences in Applied Artificial Intelligence ( Disciplinary Elective )
2022 Major in Decision Analytics ( Disciplinary Elective )
2021 Bachelor of Arts and Sciences in Applied Artificial Intelligence ( Disciplinary Elective )
2021 Major in Decision Analytics ( Disciplinary Elective )
Course to PLO Mapping 2024 Bachelor of Arts and Sciences in Applied Artificial Intelligence < PLO 1,2,3,4 >
2024 Major in Decision Analytics < PLO 1,2,3,4,5,6 >
2023 Bachelor of Arts and Sciences in Applied Artificial Intelligence < PLO 1,2,3,4 >
2023 Major in Decision Analytics < PLO 1,2,3,4,5,6 >
2022 Bachelor of Arts and Sciences in Applied Artificial Intelligence < PLO 1,2,3,4 >
2022 Major in Decision Analytics < PLO 1,2,3,4,5,6 >
2021 Bachelor of Arts and Sciences in Applied Artificial Intelligence < PLO 1,2,3,4 >
2021 Major in Decision Analytics < PLO 1,2,3,4,5,6 >
Offer in 2025 - 2026 Y        2nd sem    Examination No Exam     
Offer in 2026 - 2027 Y
Course Grade A+ to F
Grade Descriptors
A Demonstrate thorough mastery at an advanced level of extensive knowledge and skills required for attaining all the course learning outcomes. Show strong analytical and critical abilities and logical thinking, with evidence of original thought, and ability to apply knowledge to a wide range of complex, familiar and unfamiliar situations. Apply highly effective organizational and presentational skills.
B Demonstrate substantial command of a broad range of knowledge and skills required for attaining at least most of the course learning outcomes. Show evidence of analytical and critical abilities and logical thinking, and ability to apply knowledge to familiar and some unfamiliar situations. Apply effective organizational and presentational skills.
C Demonstrate general but incomplete command of knowledge and skills required for attaining most of the course learning outcomes. Show evidence of some analytical and critical abilities and logical thinking, and ability to apply knowledge to most familiar situations. Apply moderately effective organizational and presentational skills.
D Demonstrate partial but limited command of knowledge and skills required for attaining some of the course learning outcomes. Show evidence of some coherent and logical thinking, but with limited analytical and critical abilities. Show limited ability to apply knowledge to solve problems. Apply limited or barely effective organizational and presentational skills.
Fail Demonstrate little or no evidence of command of knowledge and skills required for attaining the course learning outcomes. Lack of analytical and critical abilities, logical and coherent thinking. Show very little or no ability to apply knowledge to solve problems. Organization and presentational skills are minimally effective or ineffective.
Communication-intensive Course N
Course Type Lecture-based course
Course Teaching
& Learning Activities
Activities Details No. of Hours
Lectures 36.0
Tutorials 12.0
Reading / Self study 100.0
Assessment Methods
and Weighting
Methods Details Weighting in final
course grade (%)		 Assessment Methods
to CLO Mapping
Presentation oral presentation and in-class discussion 50.0 1,2,3,4
Project reports written report 50.0 1,2,3,4
Required/recommended reading
and online materials		 Yau, Nathan (2011). Visualize This: The FlowingData Guide to Design, Visualization, and Statistics. Wiley.
Tufle, Edwards R. (2001). The Visual Display of Quantitative Information. 2nd edition, Graphics Press.
Chang, Winston (2013). R Graphics Cookbook. O Reilly Media.
Murray, Dan (2013). Tableau Your Data!: Fast and Easy Visual Analysis with Tableau Software. Wiley.
King, Ritchie, S. (2014). Visual Storytelling with D3: An Introduction to Data Visualization in JavaScript. Addison-Wesley.
Course Website http://moodle.hku.hk
Additional Course Information