Same as SDS 220. An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basis requirement for biological science, engineering, environmental science, neuroscience and psychology.

Same as MTH 220. (Formerly MTH 245). An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data.

Same as SDS 220. An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data. MTH 220 satisfies the basis requirement for biological science, engineering, environmental science, neuroscience and psychology.

Same as MTH 220. (Formerly MTH 245). An application-oriented introduction to modern statistical inference: study design, descriptive statistics; random variables; probability and sampling distributions; point and interval estimates; hypothesis tests, resampling procedures and multiple regression. A wide variety of applications from the natural and social sciences are used. Classes meet for lecture/discussion and for a required laboratory that emphasizes analysis of real data.

(Formerly MTH/PSY 201 and MTH/PSY 190). An overview of the statistical methods needed for undergraduate research emphasizing methods for data collection, data description and statistical inference including an introduction to study design, confidence intervals, testing hypotheses, analysis of variance and regression analysis. Techniques for analyzing both quantitative and categorical data are discussed. Applications are emphasized, and students use R for data analysis. Classes meet for lecture/discussion and a required laboratory that emphasizes the analysis of real data.

(Formerly MTH/PSY 201 and MTH/PSY 190). An overview of the statistical methods needed for undergraduate research emphasizing methods for data collection, data description and statistical inference including an introduction to study design, confidence intervals, testing hypotheses, analysis of variance and regression analysis. Techniques for analyzing both quantitative and categorical data are discussed. Applications are emphasized, and students use R for data analysis. Classes meet for lecture/discussion and a required laboratory that emphasizes the analysis of real data.

(Formerly MTH/PSY 201 and MTH/PSY 190). An overview of the statistical methods needed for undergraduate research emphasizing methods for data collection, data description and statistical inference including an introduction to study design, confidence intervals, testing hypotheses, analysis of variance and regression analysis. Techniques for analyzing both quantitative and categorical data are discussed. Applications are emphasized, and students use R for data analysis. Classes meet for lecture/discussion and a required laboratory that emphasizes the analysis of real data.

An introduction to data science using Python, R and SQL. Students learn how to scrape, process and clean data from the web; manipulate data in a variety of formats; contextualize variation in data; construct point and interval estimates using resampling techniques; visualize multidimensional data; design accurate, clear and appropriate data graphics; create data maps and perform basic spatial analysis; and query large relational databases. No prerequisites, but a willingness to write code is necessary.

This course is an introduction to the ideas and practices of contemporary Hinduism, with an emphasis on how Hindu identities have been constructed and contested, and how they have been mobilized in culture and politics. Materials to be considered include philosophical writings, ritual texts, devotional poetry, comic books, legal treatises, personal memoirs, as well as ethnographic and popular films.

How does one make sense of what one sees in South Asia? What is the visual logic behind the production and consumption of images, advertising and film? This course considers the visual world of South Asia, focusing in particular on the religious dimensions of visuality. Topics include the divine gaze in Hindu and Buddhist contexts, the role of god-posters in religious ritual and political struggle, the printed image as contested site for visualizing the nation, and the social significance of clothing as well as commercial films.