Course Calender

Course Calender

CUSA1026 Statistical Modeling and Big Data Analytics 統計模型及大數據分析
Course Outline:
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(Last update on: 26 April 2022)



Key facts for Summer 2022:

Date:   16, 23, 30* July 2022 (14 hours)
Time:   09:30am – 1:00pm; 2:00pm –5:30pm
Teaching Platform:   Online (Zoom)
Enrollment:   30
Expected applicants:   Students who are studying S4-S5with good knowledge in mathematics
Tuition Fee:   HKD 2,940.00
Lecturer:   Dr. LEE Pak Kuen Philip
* This date is reserved for make-up classes in case there is any cancellation of classes due to unexpected circumstances.
# This course will be offered online lessons via zoom platform.


Data from various fields, such as climatology, finance and sports, exhibit different properties. This course aims to use the R-package (a statistical software) to visualize the properties of the data, fit the data into various statistical models, assess model performance and predict the data. Topics include exploratory data analysis, time series models, hidden Markov models, classification trees, Poisson process and analysis of big data problems. Students will gain hands-on experience in statistical programming at the computer lab.



Organising units:
  • Department of Statistics, CUHK
  • Centre for Promoting Science Education, CUHK
Category:   Category II – Academy Credit-Bearing
Learning outcomes:   Upon completion of this course, students should be able to:
  1. Understand data from various fields
  2. Apply the exploratory data analysis (EDA) to visualize the properties of the data;
  3. Understand the theories behind various statistical models, and how the models can be fitted into different data sets;
  4. Write computer programs in R to perform various statistical analysis;
  5. Develop a systematic approach in solving statistical problems;
Learning Activities:
  1. Lectures
  2. Lab
Medium of Instruction:   Cantonese supplemented with English
  1. Short answer test or exam
Recognition:   No. of Academy unit(s) awarded: 1
* Certificate or letter of completion will be awarded to students who attain at least 75% attendance and pass the assessment (if applicable)
Expected applicants:   Students who are studying S4-S5with good knowledge in mathematics
Organising period:   Summer 2019; Summer 2020; Summer 2021; Summer 2022
Application method:   SAYT Online application