SDST3620 Modern nonparametric statistics (6 credits) Academic Year 2025
Offering Department SCDS (Department of Statistics and Actuarial Science) Quota ---
Course Co-ordinator Dr C Zhang, SCDS (Department of Statistics and Actuarial Science) < zhangcys@hku.hk >
Teachers Involved (Dr C Zhang,Statistics & Actuarial Science)
Course Objectives The course aims to acquaint students with the fundamentals, basic properties and use of classical and modern nonparametric statistical methods for data analysis.
Course Contents & Topics Topics may include: order-statistics; goodness-of-fit tests; rank tests for  single-sample and two-independent samples; tests for designed experiments; permutation tests; tests for trends and association; jackknife and bootstrapping methods; nonparametric regression.
Course Learning Outcomes
On successful completion of this course, students should be able to:

CLO 1 identify appropriate nonparametric methods for analyzing data
CLO 2 perform a variety of nonparametric statistical analyses
CLO 3 gain a working proficiency in the use of statistical software for data management and performing basic nonparametric statistical analyses
CLO 4 effectively communicate findings and conclusions
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 Major in Decision Analytics ( Disciplinary Elective )
2024 Major in Statistics ( Disciplinary Elective )
2024 Minor in Statistics ( Disciplinary Elective )
2023 Major in Decision Analytics ( Disciplinary Elective )
2023 Major in Statistics ( Disciplinary Elective )
2023 Minor in Statistics ( Disciplinary Elective )
2022 Major in Decision Analytics ( Disciplinary Elective )
2022 Major in Statistics ( Disciplinary Elective )
2022 Minor in Statistics ( Disciplinary Elective )
2021 Major in Decision Analytics ( Disciplinary Elective )
2021 Major in Statistics ( Disciplinary Elective )
2021 Minor in Statistics ( Disciplinary Elective )
Course to PLO Mapping 2024 Major in Decision Analytics < PLO 1,2,3,4 >
2024 Major in Statistics < PLO 1,2,4,5,6 >
2023 Major in Decision Analytics < PLO 1,2,3,4 >
2023 Major in Statistics < PLO 1,2,4,5,6 >
2022 Major in Decision Analytics < PLO 1,2,3,4 >
2022 Major in Statistics < PLO 1,2,4,5,6 >
2021 Major in Decision Analytics < PLO 1,2,3,4 >
2021 Major in Statistics < PLO 1,2,4,5,6 >
Offer in 2025 - 2026 Y        1st sem    Examination Dec     
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
Assignments Coursework (assignments, tutorials and a class test) 50.0 1,2,3,4
Examination One 2-hour written examination 50.0 1,2,3
Required/recommended reading
and online materials		 Alvo, M. and Yu, P.L.H.: Statistical Methods for Ranking Data (Springer, 2014)
Gibbons, J.D. and Chakraborti, S.: Nonparametric Statistical Inference, 5th edition (CRC press, 2011)
Higgins, James: Introduction to Modern Nonparametric Statistics (Duxbury Press, 2004)
Sprent, P. and Smeeton, N.C.: Applied Nonparametric Statistical Methods, 4th edition (CRC press, 2007)
Wasserman, L.: All of Nonparametric Statistics (Springer, 2016)
Course Website http://moodle.hku.hk
Additional Course Information