Enquiry for Major/Minor/Programme Requirements

Major Title Major in Statistics
Offered to students admitted to Year 1 in 2017-2018
Objectives:

The Major in Statistics focuses on the study of statistics, a scientific discipline characterized by the development and applications of analytical and quantitative tools which involve logical thinking, problem formulation, probability reasoning and intensive data analyses. The programme aims to equip students with powerful mathematical, analytical and computational skills, which are in great demand in practical areas where data are obtained for the purpose of extracting information in support of decision making. It gives students a strong background in statistical concepts, and provides broad and solid training in applied statistical methodologies. The curriculum is constantly revised to meet a steadily rising demand for specialist statisticians or quantitative analysts in government, business, finance, industry, as well as in research and teaching in local and overseas institutions.

Learning Outcomes:
By the end of this programme, students should be able to:
PLO 1 :

receive solid training in probability and statistics, gain insight into their underlying theory and be acquainted with their state-of-the-art applications in the modern world (by means of coursework, tutorial classes and/or project-based learning in the curriculum)

PLO 2 :

conduct meticulous data analyses, supported by rigorous statistical reasoning, to make informed decisions in the face of uncertainty that arises in all sorts of institutions and companies, and appraise the related ethical issues (by means of coursework, tutorial classes and/or project-based learning in the curriculum)

PLO 3 :

equip with hands-on experience in data analysis using commercial statistical software, and be competent for data-analytic jobs which require advanced computational skills (by means of coursework, tutorial classes and/or project-based learning in the curriculum)

PLO 4 :

be highly motivated to explore cross-disciplinary applications of statistics in a broad variety of academic or professional areas including, in particular, mathematics, natural sciences, economics, finance, business, risk management, actuarial work, social sciences and engineering (by means of coursework, tutorial classes and/or project-based learning in the curriculum)

PLO 5 :

communicate and collaborate with people effectively on probability and statistical issues (by means of coursework, tutorial classes, project-based and/or capstone learning in the curriculum)

PLO 6 :

through the understanding and application of statistical concepts and techniques, gain confidence to meet challenges posed by increasingly complicated real-life problems encountered in the modern era in a creative and rational manner (by means of coursework, tutorial classes, project-based and/or capstone learning in the curriculum)

Impermissible Combination:

Major in Computing and Data Analytics
Major in Decision Analytics
Major in Risk Management
Minor in Risk Management
Minor in Statistics

Required courses (96 credits)
1. Introductory level courses (42 credits)
Disciplinary Core Courses: Science Foundation Courses (12 credits)
SCNC1111 Scientific method and reasoning (6)
SCNC1112 Fundamentals of modern science (6)
Disciplinary Core Courses (30 credits)
MATH1013 University mathematics II (6)
STAT1600 Statistics: ideas and concepts (6)
MATH2014 Multivariable calculus and linear algebra (6)
STAT2601 Probability and statistics I (6)
STAT2602 Probability and statistics II (6)
2. Advanced level courses (48 credits)
Disciplinary Core Courses (24 credits)
STAT3600 Linear statistical analysis (6)
STAT3603 Probability modelling (6)
STAT4601 Time-series analysis (6)
STAT4602 Multivariate data analysis (6)
Disciplinary Electives (24 credits)
At least 24 credits from Lists A and B, among which at least 6 credits from List A:
List A
STAT3602 Statistical inference (6)
STAT3604 Design and analysis of experiments (6)
STAT3620 Modern nonparametric statistics (6)
STAT3621 Statistical data analysis (6)
List B
STAT3605 Quality control and management (6)
STAT3606 Business logistics (6)
STAT3607 Statistics in clinical medicine and bio-medical research (6)
STAT3608 Statistical genetics (6)
STAT3612 Data mining (6)
STAT3613 Marketing engineering (6)
STAT3616 Advanced SAS programming (6)
STAT3617 Sample survey methods (6)
STAT3955 Survival analysis (6)
3. Capstone requirement (6 credits)
At least 6 credits selected from the following courses:
STAT3799 Directed studies in statistics (6)
STAT4710 Capstone experience for statistics undergraduates (6)
STAT4766 Statistics internship (6)
STAT4799 Statistics project (12)
 
Notes:

1. Students who wish to specialize in the theme of data science are recommended to choose the combination of courses STAT3612, STAT3613, STAT3616 and STAT3621. Note that students who wish to take STAT3616 and STAT3621 are strongly recommended to take STAT2603 first.

2. Double-counting of courses up to a maximum of 24 credits is permissible when a student with a science major opts to undertake a second major in science. The double-counted courses must include SCNC1111 Scientific method and reasoning (6 credits) and SCNC1112 Fundamentals of modern science (6 credits). Additional credits to be double-counted must be for courses required ('disciplinary core') by both majors. For cases with 24 or less double-counted credits, the student must make up an equivalent number of credits by taking other courses offered by any Faculty.

3. If more than 24 credits (including SCNC1111 & SCNC1112) are listed as required courses ("disciplinary core") in both the first and second majors undertaken by a student, the student must make up the number of credits above the 24 permissible by taking replacement course(s) (disciplinary electives) in the second major. Double counting of credits is not permissible for major-minor or double-minors combinations. For details, please refer to "Students taking double Majors, Major-Minor or double Minors with overlapping course requirements" in the BSc syllabuses.

4. Students are not required to take Capstone if this Science major is taken as a second major on the condition that the capstone experience in the first major requires the integration or application of knowledge from both major disciplines.  If this is approved, a 6-credit advanced level course (disciplinary electives) in the second major must be taken to fulfill the credit requirement of the capstone experience.

5. Students must have level 2 or above in HKDSE Extended Module 1 or 2 of Mathematics or equivalent to take this major.  Students who do not fulfill this requirement are advised to take MATH1011 University mathematics I.

6. Students taking the Mathematics related major/minor should check the exemption and replacement arrangement for the introductory level Disciplinary Core Mathematics courses at http://www.scifac.hku.hk/ug/current/bsc/curriculum/overlapping-course-req.

Remarks:

Important! Ultimate responsibility rests with students to ensure that the required pre-requisites and co-requisite of selected courses are fulfilled. Students must take and pass all required courses in the selected primary science major in order to satisfy the degree graduation requirements.



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