220050 SE SE Advanced Data Analysis 2 (2017S)

Course Objectives and Summary:

1. To develop a clear conceptual understanding of simple and multiple regression, logistic regression, multinomial regression, and multilevel linear modeling. Other topics in linear models may be introduced as time allows.

2. To acquire skills of developing and testing aforementioned statistical models. At the end of the course, you should be able to correctly formalize your theoretical hypotheses, apply statistical tests, identify model assumptions, interpret model parameters, and perform model comparisons.

3. To gain practical experience in using various statistical software such as SPSS or R to test the aforementioned statistical models.

This course is the second in the three-course methodology sequence required of all students enrolled in the M.A. in Research Master Communication Science program. The course covers an introduction to the analysis of data using the general linear models and serves as a foundation for more advanced statistical methods courses offered throughout the university.

Focus is on conceptual understanding rather than mathematical computation. Students will gain experience practicing their learning through various assignments using SPSS and R with an emphasis on writing the “code” or “syntax” rather than the use of the point-and-click interface. The course will take the form of interactive workshop sessions, placing particular emphasis on student participation. Theoretical discussion of key issues will be accompanied with examples taken from literature and practical exercises.