Statistical and Data Sciences 300 - Applications of Statistics and Data Science: Statistics in Education

Conclusions drawn from data are useful only when they are interpreted in the appropriate context. Appreciating such context often requires expertise in a particular knowledge domain. Many courses outside of the program provide students with opportunities to conduct a substantial data analysis project and have that work evaluated by a domain expert. This course provides that opportunity for knowledge domains specific to program faculty. Topics may include public health, sports analytics, music information retrieval, ecology, etc. This course always counts towards the application domain requirement for the major and may be repeated for credit with different topics: Students will learn educational measurement and assessment, and apply this knowledge to a research project analyzing educational data. Discussions will cover sensitivity and specificity, reliability, validity, item response theory, logistic regression, and the Rasch model. Students will use this knowledge to evaluate the effectiveness of a new curriculum on the performance of at-risk low-income students. Research will also be conducted on an additional dataset to analyze the relationship between student/family characteristics and educational outcomes.

Instructor Permission.