SDST1600 Statistics: Ideas and Concepts (6 credits) Academic Year 2026
Offering Department SCDS (Department of Statistics and Actuarial Science) Quota ---
Course Co-ordinator Dr C W Kwan, SCDS (Department of Statistics and Actuarial Science) < cwkwan@hku.hk >
Teachers Involved (Dr C W Kwan,Statistics & Actuarial Science)
(Prof M B Zhu,Statistics & Actuarial Science)
Course Objectives The course aims at providing a broad overview of statistics for students who aspire to study in BStat or major in Decision Analytics, Risk Management, or Statistics. It focuses on the roles of statistics as a scientific tool with applications to a wide spectrum of disciplines, and as a science of reasoning which has revolutionized modern intellectual endeavours. It lays a panoramic foundation for a formal study of statistics at the university level.
Course Contents & Topics - Data collection: observational studies versus designed experiments
- Data presentation: tables; graphs; frequency distributions; correlations; trends
- Probability: randomness; probability models; distributions; measures of central tendency and dispersion
- Inference: estimation; tests of significance and hypotheses; confidence intervals; regression; prediction
- Further issues: controversies; misuse of statistics; ethics.
Course Learning Outcomes
On successful completion of this course, students should be able to:

CLO 1 understand the role of statistics as a tool for scientific reasoning
CLO 2 present data in a useful and informative way
CLO 3 acquire basic concepts and perspectives of statistical modelling and inference
CLO 4 distinguish between good and bad statistical practices
CLO 5 pursue a study in BStat or a major study in Decision Analytics, Risk Management or Statistics, or with a well-established conceptual foundation
Pre-requisites
(and Co-requisites and
Impermissible combinations)		 Not for students who have passed in any of the following courses: MATH1853, SDST1602, SDST1603, SDST2602, SDST3902.
Only for students admitted in 2025 and thereafter.
Course Status with Related Major/Minor /Professional Core 2026 Professional Core in Decision Analytics ( Core/Compulsory )
2026 Professional Core in Risk Management ( Core/Compulsory )
2026 Professional Core in Statistics ( Core/Compulsory )
2026 Major in Chemistry (Intensive) ( Disciplinary Elective )
2026 Major in Decision Analytics ( Core/Compulsory )
2026 Major in Physics (Intensive) ( Disciplinary Elective )
2026 Major in Risk Management ( Core/Compulsory )
2026 Major in Statistics ( Core/Compulsory )
2026 Minor in Risk Management ( Disciplinary Elective )
2026 Minor in Statistics ( Disciplinary Elective )
2025 Professional Core in Decision Analytics ( Core/Compulsory )
2025 Professional Core in Risk Management ( Core/Compulsory )
2025 Professional Core in Statistics ( Core/Compulsory )
2025 Major in Chemistry (Intensive) ( Disciplinary Elective )
2025 Major in Decision Analytics ( Core/Compulsory )
2025 Major in Physics (Intensive) ( Disciplinary Elective )
2025 Major in Risk Management ( Core/Compulsory )
2025 Major in Statistics ( Core/Compulsory )
2025 Minor in Risk Management ( Disciplinary Elective )
2025 Minor in Statistics ( Disciplinary Elective )
Course to PLO Mapping 2026 Professional Core in Decision Analytics < PLO 1,2,4,5,6 >
2026 Professional Core in Risk Management < PLO 2,3,4,5,6 >
2026 Professional Core in Statistics < PLO 1,2,4,5,6 >
2026 Major in Chemistry (Intensive) < PLO 4,5 >
2026 Major in Decision Analytics < PLO 1,2,4,5,6 >
2026 Major in Physics (Intensive) < PLO 2,3,4 >
2026 Major in Risk Management < PLO 2,3,4,5,6>
2026 Major in Statistics < PLO 1,2,4,5,6>
2025 Professional Core in Decision Analytics < PLO 1,2,4,5,6 >
2025 Professional Core in Risk Management < PLO 2,3,4,5,6 >
2025 Professional Core in Statistics < PLO 1,2,4,5,6 >
2025 Major in Chemistry (Intensive) < PLO 4,5 >
2025 Major in Decision Analytics < PLO 1,2,4,5,6 >
2025 Major in Physics (Intensive) < PLO 2,3,4 >
2025 Major in Risk Management < PLO 2,3,4,5,6>
2025 Major in Statistics < PLO 1,2,4,5,6>
Offer in 2026 - 2027 Y        1st sem    2nd sem    Examination Dec    May     
Offer in 2027 - 2028 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
Assignments Coursework (assignments, class test(s) and project(s)) 60.0 1,2,3,4,5
Examination One 2-hour written examination 40.0 1,2,3,4,5
Required/recommended reading
and online materials		 Utts, J.M. (2014). Seeing Through Statistics (4th edition). Cengage Learning.
Heckard, R.F. and Utts, J.M. (2012).  Statistics (International edition, 4th edition). Cengage Learning.
Albright, S. C., Winston, W. L. and Zappe, C. J. (2009). Data Analysis and Decision Making with Microsoft Excel. Cengage Learning.
Moore, D. S. and Notz, W. I. (2006). Statistics: Concepts and Controversies. Freeman: New York.
Course Website http://moodle.hku.hk
Additional Course Information NIL