Professional seminar to support students in Early Childhood Education field experience practica.

This is a course in comparative capitalism. It will review important debates and frameworks that have been advanced to understand the variations in the economic systems of different capitalist economies. We will review some classical work from Marx and Weber, as well as the distinction between liberal, coordinated and state-led systems. We will examine a number of case-studies, including the U.S., Sweden, France, Japan, South Korea and Russia.

Computational social scientists are increasingly leveraging the wealth of digital text along with powerful computing resources for the analysis of "text-as-data." In this 3-credit graduate course, we tackle advanced approaches for the systematic analysis of text, starting with general principles and progressing through a variety of approaches that better account for the complexity of text than simple bag-of-words models.. We'll explore more sophisticated representations like word embeddings, both static and contextual, and their applications in social science research.

This course gives students the tools to collect, organize, cleanse, format, integrate and transform their data so that it is ready for analytical work in the social sciences. The course covers R and Python in parallel, so that students become familiar with these popular and powerful languages, while comparing that each one offers for the pre processing stage.

This course introduces students to spatial analytics using both GIS and R, with primary focus on social scientific research, social justice concerns as well as social and public policy related inquiries. Exposure would also be given to the theoretical underpinnings of robust analysis as they pertain to spatial data analytics. Descriptive statistics in the context of spatial data would be the focus of the first third of the term, followed by an introduction to OLS and relevant estimation aims such as minimization of residuals.

This course is intended as a math "boot camp" for incoming DACSS students and PhD students in certain social and behavioral sciences. Students will develop or refresh math skills needed for effectively learning applied statistics and computational methods. Topics covered include essential algebra review (basic skills, functions, exponents and logarithms, trigonometric functions); key concepts from calculus and their applied use; probabilistic reasoning, calculation, and distribution functions; and fundamentals of matrix arithmetic and linear algebra.

This course provides a comprehensive introduction to medical physiology, focusing on the mechanisms that underlie the function of the mammalian organism. Topics include the structure and function of major organ systems, including the nervous, muscular, cardiovascular, respiratory, renal, digestive, endocrine, and reproductive system. Emphasis is placed on maintenance of homeostasis, cellular communication, and the integration of body systems in health and disease.

Managerial accounting for non-accountants. Focus is on the use of accounting information to improve planning and control activities in business enterprises. Topics include determining the costs of products and services, assessing product and project profitability, and budgeting and monitoring costs and profits. Prerequisite: ACCOUNTG 221.