The field of applied statistics focuses on quantitative methods that aid in inferring statistical results and analyzing complex data in a business environment. This course introduces the basic concepts and methods of data science. We will demonstrates basic methods of data analysis, such as t-test, regression, ANOVA, factor analysis, structural equation modelling (SEM), etc.
To conceptually understand the basic ideas of applied statistics and data analysis, we will properly apply these applied statistics methods to real world problems using IBM SPSS (a statistical software), and draw valid conclusions.
You will also formulate, solve, and interpret mathematical models from various applications areas in applied statistics. This course will require the use of personal computers and spreadsheet-based software (SPSS). On SEM, we will use LISREL or AMOS software to introduce confirmatory analysis, second order factor analysis, multiple group analyses, structual model testing, mediating and moderating effect testing, ect.The field of applied statistics focuses on quantitative methods that aid in inferring statistical results and analyzing complex data in a business environment. This course introduces the basic concepts and methods of data science. We will demonstrates basic methods of data analysis, such as t-test, regression, ANOVA, factor analysis, structural equation modelling (SEM), etc.
To conceptually understand the basic ideas of applied statistics and data analysis, we will properly apply these applied statistics methods to real world problems using IBM SPSS (a statistical software), and draw valid conclusions.
You will also formulate, solve, and interpret mathematical models from various applications areas in applied statistics. This course will require the use of personal computers and spreadsheet-based software (SPSS). On SEM, we will use LISREL or AMOS software to introduce confirmatory analysis, second order factor analysis, multiple group analysis, structural model testing, mediating and moderating effect testing, ect.
Required 1: Hair et al. (2006), Multivariate Data Analysis (7th), Prentice Hall
Required 2: 蕭文龍 (2009), 多變量分析最佳入門實用書(第二版)：SPSS+LISREL, 碁峰
Recommended: 邱皓政 (2011)，量化研究與統計分析-SPSS資料分析範例(第五版)，五南
Required 1: Hair et al. (2006), Multivariate Data Analysis (7th), Prentice Hall
Required 2: Zi Wenlong (2009), Best Practical Book for Multivariate Analysis (Second Edition): SPSS+LISREL, Qi Feng
Recommended: Qiu Haozheng (2011), Quantitative Research and Statistical Analysis-SPSS Data Analysis Example (Fifth Edition), Wunan
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| 基礎統計與多變量分析（楊老師）基礎統計與多變量分析（楊老師） Basic statistics and multivariate analysis (Teacher Yang) |
50 | 作業10%, 期中考35%, 其他5% |
| 結構方程模式（黃老師）結構方程模式（黃老師） Constructed equation pattern (Teacher Huang) |
50 | 作業與報告30%，上機測驗及期末報告20% |
