A continuation of 110. One 50-minute musicianship section required per week, in addition to classroom meetings. Prerequisite: 110 or permission of the instructor. Enrollment limited to 18.

This course explores different approaches to the study of music as a cultural phenomenon. We consider basic questions, such as: Why is music so often at the center of our most profound personal and social experiences? Why is music a fundamental means of connecting with our own lives, our communities and the wider world in which we live?

The primary goal of this course is to deepen your understanding of the music you like, while forging connections to music that is unfamiliar to you, making you a more well-informed music consumer. Throughout the course, you hone active listening skills, helping you to identify technical components and to connect with the music on an emotional level. These skills help you describe more specifically what you hear, and decode increasingly complex music. Classes cover folk, popular, jazz, non-western classical and other styles.

Colloquia are especially designed for those with no previous background in music. Limited to 20 students, they emphasize class discussion and written work, which consists of either music or critical prose as appropriate to the topic. Open to all students, but particularly recommended for first-year students and sophomores.: An introduction to music notation and to principles of musical organization, including scales, keys, rhythm and meter. Limited to beginners and those who did not place into 110.

Sectioned course.: This course provides an introduction to physical conditioning through the sport of ultimate frisbee. Students will learn how to build endurance, speed, quickness, and agility while developing a basic understanding of ultimate’s rules and fundamental skills.  This course is for all people looking to improve physical fitness in the fun, encouraging environment ultimate provides. Enrollment limited to 25.

Topics in statistics and data science. Statistical methods for analyzing data must be chosen appropriately based on the type and structure of the data being analyzed. The particular methods and types of data studied this in this course vary, but topics may include: categorical data analysis, time series analysis, survival analysis, structural equation modeling, survey methodology, Bayesian methods, resampling methods, spatial statistics, missing data methods, advanced linear models, statistical/machine learning, network science, relational databases, web scraping and text mining.

Same as SDS 291. Formerly MTH 247. Theory and applications of regression techniques; linear and nonlinear multiple regression models, residual and influence analysis, correlation, covariance analysis, indicator variables and time series analysis. This course includes methods for choosing, fitting, evaluating and comparing statistical models and analyzes data sets taken from the natural, physical and social sciences. Prerequisite: one of the following: PSY 201, GOV 190, MTH 220, ECO 220, or the equivalent or a score of 4 or 5 on the AP Statistics examination. Enrollment limited to 25.

Same as MTH 291. Formerly MTH 247. Theory and applications of regression techniques; linear and nonlinear multiple regression models, residual and influence analysis, correlation, covariance analysis, indicator variables and time series analysis. This course includes methods for choosing, fitting, evaluating and comparing statistical models and analyzes data sets taken from the natural, physical and social sciences. Prerequisite: one of the following: MTH 201/PSY 201, GOV 190, MTH 219, MTH 220, ECO 220, or the equivalent or a score of 4 or 5 on the AP Statistics examination.

Same as SDS 290. Note: This course is no longer considered the same as PSY 301, starting in the 2014–15 academic year. A survey of statistical methods needed for scientific research, including planning data collection and data analyses that provide evidence about a research hypothesis. The course can include coverage of analyses of variance, interactions, contrasts, multiple comparisons, multiple regression, factor analysis, causal inference for observational and randomized studies and graphical methods for displaying data.

Same as MTH 290. Note: This course is no longer considered the same as PSY 301, starting in the 2014–15 academic year. A survey of statistical methods needed for scientific research, including planning data collection and data analyses that provide evidence about a research hypothesis. The course can include coverage of analyses of variance, interactions, contrasts, multiple comparisons, multiple regression, factor analysis, causal inference for observational and randomized studies and graphical methods for displaying data.