傳播數據分析

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 hands-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, moderation, and conditional process analyses. In the third part, we will present confirmatory factor analysis, structural equation modeling, and cluster analysis.

Students are expected to have the following background: - Familiarity with basic statistics and R programing (at a minimum, at the level of DCT1038, or equivalent with permission of the instructor)