SDST4613 Causal Inference (6 credits) Academic Year 2025
Offering Department SCDS (Department of Statistics and Actuarial Science) Quota
Course Co-ordinator Prof E C H Fong, SCDS (Department of Statistics and Actuarial Science) < chefong@hku.hk >
Teachers Involved (Prof E C H Fong, Statistics & Actuarial Science)
Course Objectives This course will provide a rigorous introduction to modern causal inference. Students will learn how to define and identify causal effects from data, and avoid common pitfalls and misconceptions when drawing causal conclusions. The course will have a strong focus on statistical estimation, and equip students with practical tools to answer causal questions. This course is particularly suitable for students who intend to pursue further studies or a career in statistical and epidemiological research.
Course Contents & Topics Causal effect identification, confounding, selection bias, potential outcomes, causal directed acyclic graphs; randomized experiments, observational studies; treatment heterogeneity, matching; g-formula, outcome regression, inverse probability weighting, doubly robust methods; causal survival analysis; time-varying treatments, target trial emulation

Real data sets will be presented for gaining hands-on experience on causal inference techniques

Course Learning Outcomes
On successful completion of this course, students should be able to:

CLO 1 Define causal effects and specify the assumptions required for their identification
CLO 2 Identify the sources of biases that affect causal inference in observational settings
CLO 3 Estimate causal effects with modern statistical tools
CLO 4 Carry out the full causal inference pipeline within applied settings
Pre-requisites
(and Co-requisites and
Impermissible combinations)		 Pass in SDST3600 or SDST3602 or SDST3603
(Students are recommended to take SDST3607/SDST3655, and SDST3612 prior to this course)
Course Status with Related Major/Minor /Professional Core 2025 Professional Core in Decision Analytics ( Disciplinary Elective )
2025 Professional Core in Statistics ( Disciplinary Elective )
2025 Major in Decision Analytics ( Disciplinary Elective )
2025 Major in Statistics ( Disciplinary Elective )
2025 Minor in Statistics ( Disciplinary Elective )
Course to PLO Mapping 2025 Professional Core in Decision Analytics < PLO 1,2,3,4,6 >
2025 Professional Core in Statistics < PLO 1,2,3,4,6 >
2025 Major in Decision Analytics < PLO 1,2,3,4,6 >
2025 Major in Statistics < PLO 1,2,3,4,6 >
Offer in 2025 - 2026 N            Examination May     
Offer in 2026 - 2027 N
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
Assignments Coursework (assignments, tutorials, and class test(s)) 40.0 1,2,3,4
Examination One 2-hour written examination 60.0 1,2,3,4
Required/recommended reading
and online materials		 Hernán MA, Robins JM (2020). Causal Inference: What If. Boca Raton: Chapman & Hall/CRC. (https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/)
Course Website http://moodle.hku.hk
Additional Course Information