Courses taught at Penn GSE
REGRESSION AND ANALYSIS OF VARIANCE (EDUC 767)
This course covers concepts related to general linear models and will primarily
focus on topics such as correlation, regression and analysis-of-variance. We will compute examples of
many of these models to understand their applications in practice.
INTRODUCTION TO CAUSAL INFERENCE (EDUC 765)
This course offers an applied introduction to methods of causal inference for
evaluation research. The course will be organized into three sections: (i) methods for analyzing simple
randomized and cluster randomized experiments; (ii) analysis techniques for quasi-experimental and
observational studies and; (iii) advanced topics in causal inference methods.
INTRODUCTION TO STATISTICS (EDUC 667)
This course is designed to provide students with a basic foundation in the use of statistical methods for quantitative research. Throughout this course, you will learn concepts in descriptive and inferential statistics in order to read, comprehend and communicate results from methodological and applied studies in education research. In addition to developing a strong foundation in statistics, you will also learn methods for data analysis using statistical software. To this end, you will have opportunities to organize, analyze, and summarize parts of actual datasets from education. This is the first course in statistics for students preparing to become researchers in the social sciences and education, and will provide preparation for more advanced coursework in statistical methods and quantitative research (should you choose to do so).
REPLICATION AND REPRODUCIBILITY (EDUC 545)
This course provides students with an understanding of the history of replication science, the implications for current studies, and the types of statistical methods that have been proposed to address the "replication crisis." The course topics will be divided among three categories: (i) differences between the definition and analysis of replication, (ii) frameworks for replication studies and, (iii) statistical approaches based on meta-analysis for designing replication studies.