(Offered as HIST 223 [EU/ME/TC/TS/^C/^P] and SWAG 223) 

(Offered as SWAG 209, ANTH 209, and SOCI 207) This seminar uses feminist theory and methods to consider scientific practice and the production of scientific knowledge. We will explore how science reflects and reinforces social relations, positions, and hierarchies as well as whether and how scientific practice and knowledge might be made more accurate and socially beneficial.

(Offered as POSC 160 and SWAG 160) From abortion to gay rights, sexuality is deeply entangled in world politics. As LGBT rights become human rights principles, they not only enter the rights structure of the European Union and the United Nations but are also considered a barometer of political modernity. If some Latin American nations have depicted their recognition of gay rights as symbolic of their progressive character, certain North African nations have depicted their repression of homosexuality symbolic of their opposition to western imperialism.

(Offered as CLAS 123 and SWAG 123) We read in English the major authors from Homer in the 8th century BCE to Plato in the 4th century in order to trace the emergence of epic, lyric poetry, tragedy, comedy, history, and philosophy. How did the Greek enlightenment, and through it Western culture, emerge from a few generations of people moving around a rocky archipelago? How did folklore and myth develop into various forms of “rationality”: science, history, and philosophy? What are the implications of male control over public and private life and the written record?

Our world is awash in data. To allow decisions to be made based on evidence, there is a need for statisticians to be able to make sense of the data around us and communicate their findings. In this course, students will be exposed to advanced statistical methods and will undertake the analysis and interpretation of complex and real-world datasets that go beyond textbook problems.

Fall and spring semesters. The Department.

Competitions, which can include individual and team sports, eSports, tabletop gaming, preference formation, and elections, produce data dependent on interrelated competitors and the decision, league, or tournament format. In this course, students will learn to think about the ways a wide variety of statistical methodologies can be applied to the complex and unique data that emerge through competition, including paired comparisons, decision analysis, rank-based and kernel methods, and spatio-temporal methods.

(Offered as STAT 360 and MATH 360) This course explores the nature of probability and its use in modeling real world phenomena. There are two explicit complementary goals: to explore probability theory and its use in applied settings, and to learn parallel analytic and empirical problem-solving skills. The course begins with the development of an intuitive feel for probabilistic thinking, based on the simple yet subtle idea of counting. It then evolves toward the rigorous study of discrete and continuous probability spaces, independence, conditional probability, expectation, and variance.

(Offered as STAT 360 and MATH 360) This course explores the nature of probability and its use in modeling real world phenomena. There are two explicit complementary goals: to explore probability theory and its use in applied settings, and to learn parallel analytic and empirical problem-solving skills. The course begins with the development of an intuitive feel for probabilistic thinking, based on the simple yet subtle idea of counting. It then evolves toward the rigorous study of discrete and continuous probability spaces, independence, conditional probability, expectation, and variance.

Computational data analysis is an essential part of modern statistics and data science. This course provides a practical foundation for students to think with data by participating in the entire data analysis cycle. Students will generate statistical questions and then address them through data acquisition, cleaning, transforming, modeling, and interpretation. This course will introduce students to tools for data management, wrangling, and databases that are common in data science and will apply those tools to real-world applications.