ข้อมูลสำหรับทำแบบฝึกหัด (Data for practices)

1. Data for outlier detection
    1.1 Example (GSS2000.sav)
          https://drive.google.com/file/d/0B18QOrxCLeTVeU9hTUhOQy1EMzg/view?usp=sharing
    1.2 Practice: Car sale
          https://drive.google.com/file/d/0B18QOrxCLeTVcGVlTUpPYWRHMms/view?usp=sharing

2. Data for regression analysis
    2.1 Hypothesis tests (iqsize)
          https://drive.google.com/file/d/0B18QOrxCLeTVLUJnV1ozZEczZ1k/view?usp=sharing
    2.2 Training and validation/Model building (oxygen.txt)
          https://drive.google.com/file/d/0B18QOrxCLeTVVWRXa0F2YlJiNWc/view?usp=sharing
    2.3 Stepwise regression (cement.sav/cement.txt)
          1. cement.sav
          https://drive.google.com/file/d/0B18QOrxCLeTVUkVROTlSN1FRdEU/view?usp=sharing
          2. cement.txt
          https://drive.google.com/file/d/0B18QOrxCLeTVNnVLXzlkcHRSWFE/view?usp=sharing
          3. bloodpress.txt
          https://drive.google.com/file/d/0B18QOrxCLeTVNFNBc2tMSWd0azA/view?usp=sharing
3. Multicollinearity
    3.1 Correlated data (bloodpress.txt)
          https://drive.google.com/file/d/0B18QOrxCLeTVNFNBc2tMSWd0azA/view?usp=sharing
    3.2 Uncorrelated data (Uncorelated.txt)
          https://drive.google.com/file/d/0B18QOrxCLeTVazFsS1lIblc4cVk/view?usp=sharing
    3.3 Effect of correlated predictor variables (allentest.txt)
          https://drive.google.com/file/d/0B18QOrxCLeTVNjNWMEtVM1hlX0k/view?usp=sharing
    3.4 Variance Inflation Factor (cement.txt)
          https://drive.google.com/file/d/0B18QOrxCLeTVNnVLXzlkcHRSWFE/view?usp=sharing
    3.5 Exercise (usair.txt)
          https://drive.google.com/file/d/0B18QOrxCLeTValZQOXVBWnNRa28/view?usp=sharing
4. Principal Component Analysis (PCA)
    4.1 Use of PCA for indirect classification of iris flowers (iris practice for DA.sav)
          https://drive.google.com/file/d/0B18QOrxCLeTVMVBaLUVKLW40Wjg/view?usp=sharing
    4.2 Multiple linear regression based on PCA to solve multicollinearity (cement.sav)
          https://drive.google.com/file/d/0B18QOrxCLeTVNnVLXzlkcHRSWFE/view?usp=sharing
5. Factor analysis (FA) (oxygen.sav)
          https://drive.google.com/file/d/0B18QOrxCLeTVeFRuSFBhZDh4QW8/view?usp=sharing
6. Partial Least Squares Regression (PLSR)
          http://aendt.blogspot.com/2014/08/unscrambler.html
7. Cluster Analysis (CA)
          https://drive.google.com/file/d/0B18QOrxCLeTVYnhFZkdjM1RTMjQ/view?usp=sharing

ข้อมูลใช้ในการสอบกลางภาคปลาย ปีการศึกษา 2556-57

Data for mid-term examination on 7 January 2014. Download from the following link: https://drive.google.com/file/d/0B18QOrxCLeTVMGJqWU1EMXlOUWc/edit?usp=sharing

Power Points for multivariate data analysis lectures

ดาวน์โหลดไฟล์ Power points ได้ตามลิงค์ด้านล่าง
1. 0-Multivariate Data Analysis Intro.ppt
https://drive.google.com/file/d/0B18QOrxCLeTVbklOVlpabTBJWEU/edit?usp=sharing
2. 1-2018-T-test.ppt
https://drive.google.com/file/d/1pwa95WSTk6g2m52QB0C4G7xDcsX03EZ0/view?usp=sharing
3. 2-2018-New ANOVA.ppt
https://drive.google.com/file/d/1JdAt2nWPtPCZsCEHRth02ZwmhFaesbYB/view?usp=sharing
4. 3-Correlation.ppt
https://drive.google.com/file/d/0B18QOrxCLeTVclpaeTBLaU4zZVk/view?usp=sharing
5. 4-Regression analysis.ppt
https://drive.google.com/file/d/0B18QOrxCLeTVZXhjdnZPNGZCTlk/view?usp=sharing
6. 5-DetectingOutliers.ppt
https://drive.google.com/file/d/0B18QOrxCLeTVLUJQLVpUWVd0TnM/view?usp=sharing
7. 6-Mahalanobis Distance.ppt
https://drive.google.com/file/d/0B18QOrxCLeTVQUtvM1JyZmN0NVE/view?usp=sharing
8. 7-MLR-1 Journal example and how to test assumption.ppt
https://drive.google.com/file/d/1RPta1c-tYfZQL6Aa7u0JWdLlSARJdyax/view?usp=sharing
9. 8-MLR-2 Examples.ppt
https://drive.google.com/file/d/0B18QOrxCLeTVZHR5ZlhTaGgzUW8/edit?usp=sharing
10. 9-MLR-3 Stepwise.ppt
https://drive.google.com/file/d/0B18QOrxCLeTVZGd3TFk2SWpzQzA/edit?usp=sharing
11. 10-MLR-4 Model building strategy.ppt
https://drive.google.com/file/d/0B18QOrxCLeTVZEFCS0NuTHczaGc/edit?usp=sharing
12. 11-MLR-5 Multicollinearity.ppt
https://drive.google.com/file/d/0B18QOrxCLeTVZ1BOeUxGOWZIclU/view?usp=sharing
13. 11-MLR-5 Outliers and Influential Data Points.ppt
https://drive.google.com/file/d/0B18QOrxCLeTVWVdNcDJTYlN0bDg/edit?usp=sharing
14. 12-MLR-6 Outliers and Influential Data Points.ppt
https://drive.google.com/file/d/0B18QOrxCLeTVQnhWNW5NNmVKcVk/edit?usp=sharing
15. 13-PCA-Introduction.ppt
https://drive.google.com/file/d/0B18QOrxCLeTVdl9kN1BmcFgxcjg/edit?usp=sharing
16. 14-PCA-Calculation of PCs.ppt
https://drive.google.com/file/d/0B18QOrxCLeTVY1gtWkFLVEJxODg/edit?usp=sharing
17. 15-FA-Factor Analysis 1.ppt
https://drive.google.com/file/d/0B18QOrxCLeTVcGJoanVMeVd0d2c/edit?usp=sharing
18. 16-PLSR.ppt
https://drive.google.com/file/d/0B18QOrxCLeTVNFpPbTZLOHdyaDQ/edit?usp=sharing
19. 16-2 PLS Animation with Calibration
https://drive.google.com/file/d/0B18QOrxCLeTVY0FEUUphYkpQbzg/edit?usp=sharing
20. 17-Calibration and validation.ppt
https://drive.google.com/file/d/0B18QOrxCLeTVVDBtUHBQdmJRQk0/view?usp=sharing
21. 18 DA Good explanation of ouotput and equation Discriminant analysis with good equation to explain.pdf
https://drive.google.com/file/d/0B18QOrxCLeTVM3BiTFp2b0JKM3M/edit?usp=sharing
22. 18-1 Structure matrix in DA.ppt
https://drive.google.com/file/d/0B18QOrxCLeTVS3N4b2lWTnV6RkE/edit?usp=sharing
23. 19-Cluster Analysis.ppt
https://drive.google.com/file/d/0B18QOrxCLeTVSm1PeThIZ2tUVVE/view?usp=sharing