| Course Outline: (Click Icon to download !!) (Last update on: 25 April 2022) |
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Key facts for Summer 2022:
| Date: | 17, 18, 19, 22, 23, 24* August 2022 (30 hours) | |
| Time: | 9:30am – 12:30pm, 2:30pm – 5:30pm | |
| Teaching Platform: | Face to Face (The Chinese University of Hong Kong) # | |
| Enrollment: | 50 | |
| Expected applicants: | Students who are promoting to S4-S5 with good knowledge in mathematics and with strong interest in solving real problems |
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| Tuition Fee: | HKD 3,900.00 (Students who have attended all sessions will be granted a HKD 1,000 scholarship) |
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| 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. # This course is offered face-to-face lessons at CUHK campus. It may switch to online teaching in accordance with the pandemic development and the policy of the university. |
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Introduction:
Uncertainty exists in many real-life problems, ranging from stock returns to sport results to medication effects to election outcomes. Statistics offers methods to handle uncertainty with a higher precision. This course introduces ways to define, model and forecast uncertainty through real-life examples and counterintuitive phenomena. Topics include exchange paradox, Simpson’s paradox, linear regression model, non-parametric regression model, historical simulation, and k-mean clustering.
不確定性存在於許多現實生活中的問題,例子涵蓋股票回報、運動結果、藥物效果、選舉結果等。統計科學提供了具更高準定性的方法,以處理不確定性的問題。本課程以實際示例和違反直覺的現象引導,來定義、模型和預測不確定性。主題包括替換悖論,辛普森悖論,線性迴歸模型,非參數迴歸模型,歷史模擬法,k 平均演算法。
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| Category: | Category I – University Credit-Bearing | |
| Learning outcomes: | Upon completion of this course, students should be able to: | |
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| Medium of Instruction: | Cantonese supplemented with English | |
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| Recognition: | No. of University 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) |
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| Expected applicants: | Students who are promoting to S4-S5 with good knowledge in mathematics and with strong interest in solving real problems | |
| Organising period: | Summer 2021; Summer 2022 | |
| Application method: | SAYT Online application | |