傳播數據分析
Data Analytics in Communication
| 節 | 週五 |
|---|---|
2 09:00–09:50 | 傳播數據分析 HK206 3 節連堂 |
3 10:10–11:00 | |
4 11:10–12:00 |
* 根據陽明交大上課時間表所列
This course is an introduction to the general linear model. It aims to prepare students with statistical thinking and practical skills for tackling academic and real-world problems and serves as a foundation for advanced statistical courses offered throughout the university. Emphasis will be on conceptual understanding and problem solving rather than mathematical computation. This course is also a practical course and requires a good deal of hand-on work in which students practice their learning to achieve sustainable mastery of core data analytics techniques. This course is organized into three parts. In the first part, we will cover on data wrangling, analysis of variance, analysis of covariance, and multilevel modeling. In the second part, we will introduce linear regression, mediation and moderation analyses. In the third part, we will present confirmatory factor analysis, structural equation modeling, and cluster analysis.
Part 1 25% Week 6 Part 2 25% Week 11 Part 3 25% Week 17 Paper 25% Week 18
| 週次 | 主題 |
|---|---|
| 第 1 週 | Course Overview & Introduction Brief Introduction to R |
| 第 2 週 | Data Wrangling |
| 第 3 週 | One-Way Analysis or Variance Analysis of Covariance |
| 第 4 週 | Factorial Analysis of Variance |
| 第 5 週 | Repeated-Measures Analysis of Variance |
| 第 6 週 | Multilevel Modeling |
| 第 7 週 | Linear Regression Analysis I |
| 第 8 週 | Linear Regression Analysis II |
| 第 9 週 | Mediation |
| 第 10 週 | Moderation |
| 第 11 週 | Mediation and Moderation |
| 第 12 週 | Confirmatory Factor Analysis |
| 第 13 週 | Structural Equation Modeling (concepts) |
| 第 14 週 | Structural Equation Modeling (tools) |
| 第 15 週 | Structural Equation Modeling (analysis) |
| 第 16 週 | Dragon Boat Festival |
| 第 17 週 | Cluster Analysis |
| 第 18 週 | Paper Presentations |
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Hampshire, UK: Cengage. Hayes, A. F. (2006). A primer on multilevel modeling. Human Communication Research, 32(4), 385-410. doi: 10.1111/j.1468-2958.2006.00281.x Hayes, A. F. (2018). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (2nd ed.). New York: Guilford press. (The electronic version is available in the NYCU library) Lakens, D. (2013). Calculating and reporting effect sizes to facilitate cumulative science: a practical primer for t-tests and ANOVAs. Frontiers in Psychology, 4, 1-12. doi: 10.3389/fpsyg.2013.00863 Kline, R. B. (2016). Principles and practice of structural equation modeling (4th ed.). New York, NY: Guilford Press. Maxwell, S. E., Delaney, H. D., & Kelley, K. (2018). Designing experiments and analyzing data: A model comparison perspective (3rd ed.). New York, NY: Routledge. Tabachnick, B. G., & Fidell, L. S. (2019). Using multivariate statistics (7th ed.). Harlow, UK: Pearson.
- 聯絡方式
- 陶振超 taoc@nycu.edu.tw Ext. 31540 HK222 俞蘋 uping09@gmail.com Ext. 58725 HK219B 黃靜蓉 soniahuang@nycu.edu.tw Ext. 58712 HK231