本課程之目的在於訓練學生正確使用統計方法，應用於業界或其它研究領域之相關資料分析。對於分析結果之闡釋以及報告之撰寫，亦為課程訓練之重點。課程所涉及之統計方法包括多變量分析、類別資料分析、存活分析、抽樣調查、迴歸分析等。經由系上統計諮詢或其它資料來源訓練學生諮詢技巧和資料分析之能力.The purpose of this course is to train students to correctly use statistical methods for relevant data analysis in industry or other research fields. The interpretation of analysis results and the writing of reports are also the focus of course training. The statistical methods covered in the course include multivariate analysis, categorical data analysis, survival analysis, sampling survey, regression analysis, etc. Train students in consulting skills and data analysis abilities through the department of statistical consulting or other data sources.
本課程之目的在於訓練學生正確使用統計方法，應用於業界或其它研究領域之相關資料分析。對於分析結果之闡釋以及報告之撰寫，亦為課程訓練之重點。經由系上統計諮詢或其它資料來源訓練學生諮詢技巧和資料分析之能力。
The purpose of this course is to train students to correctly use statistical methods for relevant data analysis in industry or other research fields. The interpretation of analysis results and the writing of reports are also the focus of course training. Students' consulting skills and data analysis abilities are trained through the department of statistical consulting or other data sources.
1、沈葆聖(2002)，SAS 統計軟體與資料分析
2. Applied Linear Regression Models (by Kutner, Nachtsheim and Neter)
3. Design of Experiments: Statistical Principles of Research Design
and Analysis (by R. O. Kuehl)
4. Applied Multivariate Statistical Analysis (By Richard Johnson and Dean Wichern)
1. Shen Baosheng (2002), SAS statistical software and data analysis
2. Applied Linear Regression Models (by Kutner, Nachtsheim and Neter)
3. Design of Experiments: Statistical Principles of Research Design
and Analysis (by R. O. Kuehl)
4. Applied Multivariate Statistical Analysis (By Richard Johnson and Dean Wichern)
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| midtermmidterm midterm |
50 | |
| finalfinal final |
50 |
