Jewish Identity/MeToo

(Offered as RELI 261 and SWAG 239) Ranging from ancient texts to contemporary documentaries, we explore the portrayals and roles of women in Jewish tradition.  Sources include biblical and apocryphal texts; Rabbinic literature; selections from medieval commentaries; letters, diaries, and autobiographies written by Jewish women of various periods and settings; works of fiction; and visual media.

Dissecting Music Videos

This dance history course locates the intersections between dance, music, film, and identity politics by analyzing the cultural phenomenon of the American “music video” from the early 1980s to now. By considering American dance history from 1900 to the present, alongside film analysis work, students will gain an introductory understanding of how the moving body on screen intersects with identity politics related to race, class, sex, sexuality, and gender.

Black Feminist Lit Trad

(Offered as SWAG 208, BLST 345 [US], ENGL 276, and FAMS 379) Through a close reading of texts by African American authors, we will critically examine the characterization of female protagonists, with a specific focus on how writers negotiate literary forms alongside race, gender, sexuality, and class in their work. Coupled with our explication of poems, short stories, novels, and literary criticism, we will explore the stakes of adaptation in visual culture.

Women Writers of Africa

(Offered as BLST 203 [D], ENGL 216, and SWAG 203) The term “Women Writers” suggests, and perhaps assumes, a particular category. How useful is this term in describing the writers we tend to include under the frame? And further, how useful are the designations "African" and "African Diaspora"? We will begin by critically examining these central questions, and revisit them frequently as we read specific texts and the body of works included in this course.

Feminist Theory

In this course we will investigate contemporary feminist thought from a variety of disciplinary perspectives. We will focus on key issues in feminist theory, such as the sex/gender debate, sexual desire and the body, the political economy of gender, the creation of the "queer" as subject, and the construction of masculinity, among others. This course aims also to think through the ways in which these concerns intersect with issues of race, class, the environment and the nation.

LGBTQ Hist Pop Culture

(Offered as HIST 163 and SWAG 163) While LGBTQ people might seem to be everywhere in popular culture today, this course takes such representations as a starting point to examine the past. Do popular representations distort the queer past and if so, to what end?

Theoretical Statistics

(Offered as STAT 370 and MATH 370) This course examines the theory underlying common statistical procedures including visualization, exploratory analysis, estimation, hypothesis testing, modeling, and Bayesian inference. Topics include maximum likelihood estimators, sufficient statistics, confidence intervals, hypothesis testing and test selection, non-parametric procedures, and linear models.

Requisite: STAT 111 or STAT 135 and STAT 360, or consent of the instructor. Limited to 25 students. Spring semester. Professor Horton.

Epidemiology

Epidemiology is the study of the distribution and determinants of disease and health in human populations. It typically involves the analysis of multivariate observational data that pose challenges when trying to make causal conclusions. The course will focus on reasoning about cause and effect, study design, bias and missing data, models and analysis of risk, detection and classification, and modern approaches to confounding and causal inference.

Data Science

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 and wrangling that are common in data science and will apply those tools to real-world applications.

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