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CUSA1046 Patterns of Real Data and Simulated Data 真數據和模擬數據的規律
Course Outline:
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(Last update on: 16 March 2023)

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Key facts for Summer 2023:

Date:   24 – 27, 28* July 2023 (24 hours)
Time:   9:30 am – 12:30 pm & 2:00 pm – 5:00 pm
Venue:   CUHK campus
Enrollment:   30
Expected applicants:   Students who are promoting to or studying S4 – S6
Tuition Fee:   HKD 3,540.00
Lecturer:   Prof. CHAN, Kin Wai
* This date is reserved for make-up classes in case there is any cancellation of classes due to unexpected circumstances.



Introduction:

Statistics turns real data into science. It can also define rules to generate simulated "fake" data to understand nature. This course discusses both approaches of statistical analysis. Four themes are covered: (1) privacy protection, (2) stock price prediction, (3) trend inference of global temperature, and (4) cancer image data analysis. The problem in each theme is resolved by one advanced statistical methodology. The tools include randomized estimator, historical simulation, nonparametric trend estimation, and Kolmogorov–Smirnov test for distribution comparison. All topics are supplemented with computing laboratory sessions.

統計學將真實數據轉化為科學。它還可以定義規則來生成模擬的「假數據」以了解自然。本課程討論以上兩種統計分析的方法,並涵蓋四個大主題:(一)隱私保護、(二)股票價格預測、(三)全球氣溫趨勢和(四)癌症圖像數據分析。每個主題的問題都通過一種先進的統計方法來解決。這些工具包括隨機估計器、歷史模擬、非參數趨勢估計和用於分佈比較的Kolmogorov–Smirnov檢驗。所有主題都輔以計算實驗室課程。

 

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. properly define and write down simple probabilistic statements and make valid statistical claims;
  2. sensibly build simple statistical models for estimation, testing and prediction based on real data and simulated data; and
  3. interpret statistical results for a range of real-life problems.
   
Learning Activities:
  1. Lectures
  2. Lab
  3. Case Discussion
Medium of Instruction:   Cantonese supplemented with English
Assessment:
  1. Short answer test or exam
  2. Lab reports
Recognition:   No. of Academy unit(s) awarded: 1.5
* 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 promoting to or studying S4 – S6
Organising period:   Summer 2023
Application method:   SAYT Online application