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2018’ Welcome to Multivariate Statistics(II) |
Course description/Practice time/Final Exam/Term project |
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| 2. |
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Lecture 6. Discrimination and Classification Analysis(DCA) |
6.1 Introduction
6.2 DCA with two clusters |
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| 3. |
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Lecture 6. Discrimination and Classification Analysis(DCA) |
6.2 DCA with two clusters |
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| 4. |
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Lecture 6. Discrimination and Classification Analysis(DCA) |
6.3 DCA with two multivariate normal clusters |
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| 5. |
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Lecture 6. Discrimination and Classification Analysis(DCA) |
6.4 DCA with several clusters |
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| 6. |
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Lecture 6. Discrimination and Classification Analysis(DCA) |
6.5 DCA with several multivariate normal clusters |
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| 7. |
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Lecture 6. Discrimination and Classification Analysis(DCA) |
6.6 Evaluating classification function |
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| 8. |
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Lecture 6. Discrimination and Classification Analysis(DCA) |
6.11 R for DCA: Practice Time |
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| 9. |
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Lecture 7. Multidimensional Scaling(MDS) |
7.1 Introduction |
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| 10. |
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Lecture 7. Multidimensional Scaling(MDS) |
7.2 Metric MDS |
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| 11. |
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Lecture 7. Multidimensional Scaling(MDS) |
7.3 Non-metric MDS
7.6 R for MDS: Practice Time |
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| 12. |
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Lecture 8. Correspondence Analysis(CRA) |
8.1 Introduction |
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| 13. |
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Lecture 8. Correspondence Analysis(CRA) |
8.2 Simple CRA
8.3 Independence and homogeneity in CRA |
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| 14. |
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Lecture 8. Correspondence Analysis(CRA) |
8.4 Multiple CRA |
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| 15. |
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Lecture 8. Correspondence Analysis(CRA) |
8.5 MCRA of classification variables data
8.6 R for CRA: Practice Time |
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대구광역시 동구 동내로 64(동내동 1119) 우)41061
페이스북
트위터
카카오톡
네이버밴드
링크복사
