課程名稱 |
多變量統計分析 Multivariates Statistical Analysis |
開課學期 |
105-2 |
授課對象 |
理學院 應用數學科學研究所 |
授課教師 |
江金倉 |
課號 |
MATH7610 |
課程識別碼 |
221 U6160 |
班次 |
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學分 |
3.0 |
全/半年 |
半年 |
必/選修 |
選修 |
上課時間 |
星期一8,9(15:30~17:20)星期二8(15:30~16:20) |
上課地點 |
天數101天數101 |
備註 |
總人數上限:40人 外系人數限制:10人 |
Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1052MATH7610_ |
課程簡介影片 |
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核心能力關聯 |
本課程尚未建立核心能力關連 |
課程大綱
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課程概述 |
1. 資訊檢索: PageRank, Graphs, and Markov Chain (Multivariate Analysis and 4V)
2. 資本資產訂價模式(CAPM)in practice: Asset Allocation in investment (Mean-Variance Analysis, Markowitz portfolio theory): Multivariate Random Variables: Matrix Algebra, Random Vectors, Quadratic Forms, and Multinormal Distribution
3. Statistical Inferences for Multivariate Distributions
4. Dimensional Reduction: Principal component Analysis, Factor Analysis (reduce a large number of variables to smaller), and Random Projection
5. Default Probability (違約機率): Classification, Discriminant Analysis , Predicting group membership.
6. Cluster Analysis: Identify homogeneous subgroups of cases or variables based on some measure of distance.
7. Canonical Correlation Analysis |
課程目標 |
1. Learn basic techniques for analysis of multi-dimensional data and big data.
2. Study multivariate distributions, especially Gaussian distribution.
3. Understand multivariate statistical inference and applications such as
discriminant analysis and cluster analysis.
4. Discuss various methods for dimension reduction, including principal component
analysis, factor analysis, Canonical Correlation Analysis, etc. |
課程要求 |
Solid knowledge on calculus, probability and statistics.
Familiarity with linear algebra. |
預期每週課後學習時數 |
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Office Hours |
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指定閱讀 |
待補 |
參考書目 |
Flury, B. (1997) A First Course In Multivariate Statistics. Springer.
Srivastava, M. S. (2002) Methods of Multivariate Statistics. Wiley
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評量方式 (僅供參考) |
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