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 demonstrate basic methods of data analysis, such as t-test , regression, ANOVA, factor analysis, structural equation modeling (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, 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: Xiao Wenlong (2009), The Best Introductory Practical Book on 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 |
|---|---|---|
| 作業作業 Homework |
20 | |
| 專題專題 Topics |
30 | |
| 期中考期中考 midterm exam |
25 | |
| 期末考期末考 final exam |
25 |
