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Creative Writing |
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CRWR 496 - Honors
Credits: (3)
Honors study in English comprises (a) supervised reading in the field of the student’s major interest; (b) presentation two weeks before the last day of classes of the student’s graduating semester of an Honors essay or a creative writing project upon a topic approved by the departmental Honors committee; and (c) oral examination in the field of the student’s major interest. Students who have not completed may be admitted only under exceptional circumstances. Creative Writing Honors students may substitute for ENGL 494 either three 300- and/or 400-level Creative Writing courses, or two 300- and/or 400-level Creative Writing courses and a Creative Writing Independent Study (the project of the Independent Study must be different from the proposed Honors project). Creative Writing Honors involves the completion of a sustained project in creative writing. For College provisions governing the Admission to Honors, see catalog section titled Honors and Special Programs.
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Dance |
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DANC 100 - Critical Questions in Dance
Credits: (4)
College Curriculum: COLL 100
An exploration of significant questions and concepts, beliefs and creative visions, theories and discoveries in Dance for first-year students. Although topics vary, the courses also seek to improve students’ communication skills beyond the written word.
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DANC 111 - Modern I
Credits: (2)
College Curriculum: ACTV, ARTS
Domain (Anchored): ALV
Designed for the student with little or no dance background. Introduces dance as an art form and as a means of expression through both the study of movement fundamentals and creative work.
Course may be repeated with instructor permission
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DANC 150 - First-Year Seminar
Credits: (4)
College Curriculum: COLL 150
An exploration of a specific topic in Dance. A grade of C- or better fulfills the COLL 150 requirement. Although topics vary, the courses emphasize academic writing skills, reading and analysis of texts, and discussion. Sample topics might include various aspects of Dance History (e.g. specific choreographers or movements).
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DANC 201 - Reconstructing Moments in History
Credits: (4)
College Curriculum: COLL 200
Domain (Anchored): ALV
Domain (Reaching Out): CSI
This historical and practical chourse will explore 20th Century modern dance choreographers and the social, political, and cultural events that shaped their work. Students will also explore short excerpts from historical dancd works from notation score and create their own mini-scores using Motif Writing.
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DANC 211 - Modern II
Credits: (2)
College Curriculum: ACTV, ARTS
Designed to strengthen technical skill at an intermediate level. Explores dance as an art form and as a means of expression through both the development of movement skills and creative work.
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DANC 212 - Modern II
Credits: (2)
College Curriculum: ACTV, ARTS
Designed to strengthen technical skill at an intermediate level. Explores dance as an art form and as a means of expression through both the development of movement skills and creative work.
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DANC 220 - History of Modern Dance
Credits: (3)
Domain (Anchored): ALV
An introduction through films and lectures to the field of modern dance, which is rooted in American culture, with emphasis on the stylistic approach and aesthetic of the artists who have contributed to its development in the twentieth century.
Cross-listed with: AMST 240
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DANC 230 - History of American Vernacular Dance
Credits: (3)
An introduction, through films and lectures, to dance in U.S. popular culture with an emphasis on its development from roots in African dance to the vernacular forms of tap, ballroom, and jazz by examining the movement styles found in concert jazz, musical theatre, and popular social dances.
Cross-listed with: AFST 334 , AMST 241
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DANC 261 - Intermediate Ballet
Credits: (2)
College Curriculum: ACTV, ARTS
Domain (Anchored): ALV
Designed to strengthen technical skill at an intermediate level. Explores ballet as an art form and as a means of expression through both the development of a movement style and creative work.
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DANC 262 - Intermediate Ballet
Credits: (2)
College Curriculum: ACTV, ARTS
Domain (Anchored): ALV
Designed to strengthen technical skill at an intermediate level. Explores ballet as an art form and as a means of expression through both the development of a movement style and creative work.
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DANC 264 - Intermediate Jazz
Credits: (2)
College Curriculum: ACTV, ARTS
Domain (Anchored): ALV
Explores jazz dance as an art form and as a means of expression through technical and creative work (choreography, improvisation). The study of various jazz and musical theatre dance styles will reflect the history of jazz and popular music.
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DANC 301 - Practicum in Dance
Credits: (1-3)
Domain (Anchored): ALV
Designed to provide an opportunity for students to fulfill needs in dance-related areas of movement experience such as improvisation, partnering, effort/shape, performance skills, teaching skills, body therapies, interdisciplinary creative work, intensive work with technique, and community outreach activities.
Course may be repeated for a maximum of 6 credits
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DANC 303 - Alexander Technique
Credits: (1)
Designed to provide students with an opportunity to refine and heighten kinesthetic sensitivity. The process of exploring the inherent design of the human body, and cooperating consciously with that design, leads to greater ease, flexibility, power, and expressiveness in all activities.
As space permits, this course may be repeated once for credit
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DANC 305 - Dance Composition I
Credits: (3)
Domain (Anchored): ALV
This course introduces elements, methods and structures of dance composition in application to the solo figure. Students will have the opportunity to experiment with movement invention; to cultivate variety, contrast, and originality in their choreographic process; and to expand their personal aesthetic range.
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DANC 306 - Dance Composition II
Credits: (3)
Prerequisite(s): DANC 305
Domain (Anchored): ALV
This course builds on the compositional elements presented in DANC 305 and offers students the opportunity to develop increasing sophistication and self-direction in their approach to choreography. The inspiration for the studies will be compositional experiments in 20th and 21st century fine and performing arts.
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DANC 311 - Modern III
Credits: (1-2)
College Curriculum: ARTS
Domain (Anchored): ALV
Designed to challenge the student by introducing complex movement sequences drawn from well-known technical vocabularies.
Course may be repeated twice for credit.
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DANC 312 - Modern III
Credits: (1-2)
College Curriculum: ARTS
Domain (Anchored): ALV
Designed to challenge the student by introducing complex movement sequences drawn from well-known technical vocabularies.
Course may be repeated twice for credit.
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DANC 313 - Intermediate-Advanced Ballet
Credits: (1)
College Curriculum: ALV, ARTS
Designed for the proficient dancer to provide a sound physical and intellectual understanding of ballet technique.
May be repeated for credit.
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DANC 314 - Intermediate-Advanced Ballet
Credits: (1)
College Curriculum: ALV, ARTS
Designed for the proficient dancer to provide a sound physical and intellectual understanding of ballet technique.
May be repeated for credit.
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DANC 321 - Performance Ensemble
Credits: (1-2)
Prerequisite(s): Successful audition
Domain (Anchored): ALV
Designed to provide an opportunity for the advanced dancer to participate in creative work and performance.
Each course may be repeated three times for credit
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DANC 322 - Performance Ensemble
Credits: (1-2)
Prerequisite(s): Successful audition
Domain (Anchored): ALV
Designed to provide an opportunity for the advanced dancer to participate in creative work and performance.
Each course may be repeated three times for credit
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DANC 330 - Internship in Dance
Credits: (1-3)
Qualified students may receive credit for a structured learning experience in a professional quality dance company or dance festival (e.g., American Dance Festival, Duke University) which provides an opportunity to apply and expand knowledge under expert supervision. Must be approved in advance as well as monitored and evaluated by the faculty.
Course may be repeated for a maximum of 6 credits
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DANC 333 - South & South East Asian Folklore Performance
Credits: (3-4)
College Curriculum: COLL 200, ACTV, ARTS
Domain (Anchored): ALV
Domain (Reaching Out): CSI
Interdisciplinary journey into the sociocultural history, aesthetics, languages, and performance of indigenous ceremony, ritual, folklore, oral literature, song, dance, and theatre in South and Southeast Asia. Students will learn to sing, dance, act, chant, and analyze material from sacred Hindu epics such as the “Ramayana” and “Mahabharata.”
Cross-listed with: AMES 333 or THEA 333
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DANC 340 - African-American and South African Movement Exchange
Credits: (3)
College Curriculum: (ACTV, GER 5, GER 6)
This is both a practical and lecture-based course that provides an introduction to the aesthetics of 20th and 21st century African-American and South African modern dance pioneers who choreographed and used dance as a means for political and social expression.
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DANC 350 - Introduction to Physical Theatre
Credits: (3)
College Curriculum: COLL 200, ARTS
Domain (Anchored): ALV
Domain (Reaching Out): CSI
This course is an introduction to storytelling through movement with content inspired by both personal and societal issues. Students will develop skills through a range of physical theatre techniques. As students develop collaborative projects, they will learn to balance individual impulses within an ensemble, use compositional tools, develop physically-inspired characters, shape their environment, and provide feedback to others. Students will present an overview of one physical theatre approach as well as engage with readings, video viewings, discussions, and written responses.
Cross-listed with: THEA 350
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DANC 401 - Group Choreography
Credits: (3)
Prerequisite(s): DANC 305 - DANC 306
Corequisite(s): DANC 401L
Students explore principles of choreographic invention for small groups and large ensembles. Problems and possibilities for movement invention involving more than one dancer are investigated as an outgrowth of
DANC 305 - DANC 306 which concentrates on composition for the solo figure.
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DANC 401L - Group Choreography Lab
Credits: (1)
Students will apply principles of choreographic invention, rehearsal and performance techniques learned in DANC 401 . Emphasis is on the choreography, teaching, rehearsal and studio performance of two original works - one for a small group and one for a large ensemble.
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DANC 406 - Independent Projects in Dance
Credits: (1-3)
Directed study of the advanced student arranged on an individual basis with credit according to the range of the proposed project. A semester of work could include either a choreographic work or a research project.
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DANC 411 - Modern IV
Credits: (1-2)
College Curriculum: ARTS
Domain (Anchored): ALV
Designed for the proficient dancer to provide a sound physical and intellectual understanding of modern dance technique. Concentrates on elements drawn from specific movement theories.
Course may be repeated three times for credit.
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DANC 412 - Modern IV
Credits: (1-2)
College Curriculum: ARTS
Domain (Anchored): ALV
Designed for the proficient dancer to provide a sound physical and intellectual understanding of modern dance technique. Concentrates on elements drawn from specific movement theories.
Course may be repeated three times for credit.
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DANC 460 - Topics in Dance
Credits: (1-3)
Exploration of a topic in dance through readings, writing, discussions, and practice (when applicable).
If there is no duplication of topic, course may be repeated for credit
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Data Science |
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DATA 100 - Critical Questions in Data Science
Credits: (4)
College Curriculum: COLL 100
An exploration of significant questions and concepts, beliefs and creative visions, theories and discoveries in Data Science for first-year students. Although topics vary, the courses also seek to improve students’ communication skills beyond the written word.
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DATA 141 - Programming for Data Science
Credits: (4)
Domain (Anchored): NQR
An introduction to computational problem solving in the context of data science and commonly used data analysis software. Students can receive credit for only one of CSCI 140, DATA 141 and CSCI 141.
Cross-listed with: CSCI 140
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DATA 150 - First-Year Seminar
Credits: (4)
College Curriculum: COLL 150
An exploration of a specific topic in Data Science. A grade of C- or better fulfills the COLL 150 requirement. Although topics vary, the courses emphasize academic writing skills, reading and analysis of texts, and discussion.
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DATA 201 - Introduction to Data Science
Credits: (3)
Prerequisite(s): CSCI 140 or CSCI 141 or DATA 141
This course will focus research design in the context of data, providing an overview of different modeling approaches, their differences, and the context(s) in which each might be most (or least) appropriate to apply. Throughout the course, students will be introduced to a variety of supervised and unsupervised machine learning techniques including methods for regression, classification, and clustering. By the end of the course, students are not expected to be an expert on any particular technique, but should exhibit a solid high-level understanding of the goals of each method and be able to determine when a particular approach would be more or less suitable to a real-world problem.
Formerly: DATA 146
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DATA 202 - Ethics in Data Science
Credits: (3)
College Curriculum: COLL 200
Domain (Anchored): CSI
Domain (Reaching Out): ALV
This course provides an introduction to critical, ethical, and moral issues surrounding data and society. It blends social and historical perspectives on data with ethics, policy, and case examples-from text analytics to self-driving cars-to help students develop a workable understanding of current ethical and moral issues in data science. The course examines the ethics and morality of studying human subjects, documenting workflows, and communicating results. Students debate issues surrounding privacy, surveillance, discrimination, transparency, responsibility, and trust throughout the data lifecycle - from collection and creation to storage and analysis to the application and sharing of data.
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DATA 301 - Applied Machine Learning
Credits: (3)
Prerequisite(s): (CSCI 140 /CSCI 141 /DATA 141 ) and (CSCI 146 /DATA 201 )
This course will focus on the technical application of machine learning algorithms, their nature, and discussions regarding the potential drawbacks and advantages of different classes of algorithms. Students entering into this course should have, at a minimum, a background in python and linear algebra. No single algorithm will be covered in great depth, and the course will place a focus on the code and implementation choices necessary for each class of algorithm. Topics covered will include probability, distributions, Monte-Carlo simulations, reinforcement learning, association rules, nonlinear regression, support vector machines, kernel SVM, variable/model selection, diagnostics for regression and classification, neural networks/deep learning, natural language processing, and various associated approaches.
Formerly: DATA 310
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DATA 302 - Databases
Credits: (3)
Prerequisite(s): CSCI 140 /CSCI 141 /DATA 141 and CSCI 146 /DATA 201
In this course students will learn about relational database design and SQL programming using Python and SQLite. Throughout the course students will demonstrate their proficiency by creating relational databases based on both real and synthetic data, and querying and updating their data using SQL. An emphasis will be placed on leveraging data validation techniques provided by SQL databases.
Formerly: DATA 311
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DATA 303 - Data Visualization
Credits: (3)
Prerequisite(s): CSCI 140 /CSCI 141 /DATA 141 and DATA 201
College Curriculum: NQR
This course provides an overview of data visualization in theory and practice, helping students understand how to produce meaningful and interpretable figures from large sets of data. Students will develop the ability to contrast different approaches to data visualization and learn how to select methods appropriate for various datasets/results. Students will also learn the technical skills required to create their own visualizations using a variety of techniques and tools.
Formerly: DATA 211
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DATA 320 - Special Topics in Algorithms
Credits: (3)
Prerequisite(s): To be determined by topic each term.
Selected topics in data science that count toward the Algorithms track. The topic to be considered will be announced prior to the beginning of the semester. A student should only be able to take this course a second time if it is covering a separate topic than other times the student has enrolled. Course may count towards other Data Science tracks if approved by the instructor.
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DATA 330 - Special Topics in Spatial Data
Credits: (3)
Prerequisite(s): To be determined by topic each term.
Selected topics in data science that count toward the Spatial Data track. The topic to be considered will be announced prior to the beginning of the semester. A student should only be able to take this course a second time if it is covering a separate topic than other times the student has enrolled. Course may count towards other Data Science tracks if approved by the instructor.
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DATA 340 - Special Topics in Data Application
Credits: (3)
Prerequisite(s): To be determined by topic each term.
Selected topics in data science that count toward the Data Applications track. The topic to be considered will be announced prior to the beginning of the semester. A student should only be able to take this course a second time if it is covering a separate topic than other times the student has enrolled. Course may count towards other Data Science tracks if approved by the instructor.
A student should only be able to take this course a second time if it is covering a separate topic than other times the student has enrolled.
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DATA 341 - Applied Time Series Analysis
Credits: (3)
Prerequisite(s): CSCI 140 /CSCI 141 /DATA 141 and CSCI 146 /DATA 201
Students will learn about and discuss relevant topics and research associated with time series analysis. The course will place a focus on the code and implementation choices necessary to perform applied time series analysis. Throughout the semester students shall replicate several time-series studies and provide replication code and analyses as part of their lab assignments. Students must apply time series skills learned throughout the course to answer their own research questions. Students shall brief progress on their projects throughout the semester as well as the final project and results during the last couple weeks of the semester.
Formerly: DATA 330
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DATA 380 - Special Topics: Non Computational Courses
Credits: (3)
Prerequisite(s): To be determined by topic each term.
Selected topics of a non-computational nature related to Data Science. The topic to be considered will be announced prior to the beginning of the semester. A student should only be able to take this course a second time if it is covering a separate topic than other times the student has enrolled. Course may count towards other Data Science tracks if approved by the instructor.
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DATA 390 - Directed Research in Data Science
Credits: (1-3)
This course is designed to permit students with a focus in Data Science to engage in directed research after completing core coursework in Data Science. Working closely with a program faculty member as an advisor, each student will conduct a substantial research project focusing on synthesis and critical analysis, to solve problems in an applied and/or academic setting, to create original material or original scholarship, and to communicate effectively with a diversity of audiences.
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DATA 420 - Special Topics: Algorithms Capstone
Credits: (3)
Selected topics in data science that count toward the Algorithms track. Course is designed to meet the capstone requirement. The topic to be considered will be announced prior to the beginning of the semester. Course may count towards other Data Science tracks if approved by the instructor.
A student should only be able to take this course a second time if it is covering a separate topic than other times the student has enrolled.
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DATA 430 - Special Topics: Spatial Data Capstone
Credits: (3)
Selected topics in data science that count toward the Spatial Data track. Course is designed to meet the capstone requirement. The topic to be considered will be announced prior to the beginning of the semester. Course may count towards other Data Science tracks if approved by the instructor.
A student should only be able to take this course a second time if it is covering a separate topic than other times the student has enrolled.
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DATA 431 - Spatial Data Discovery
Credits: (3)
Prerequisite(s): CSCI 140 /CSCI 141 /DATA 141 and (CSCI 146 /DATA 201 and GIS 201 )
College Curriculum: COLL 400
Most, if not all, of today’s grand challenges (e.g., food, water and energy security) can be described spatially from regional to global scales and, while several individual disciplines contend to address these challenges, there is one key factor that they all have in common: the need for data. Despite our being in an age rich in data, many of the critical datasets needed for our understanding and prediction of our world are, in fact, quite limited. In this capstone course, you will get the opportunity to utilize your Python programming skills (writing scripts and creating subroutines) to connect to various types of data (e.g., GeoJSON, ASC, HDF5, and NetCDF), synthesize these data to unlock new understanding (using methods such as spatial scaling and gap-filling), create visualizations using open-source GIS software, and present to the world your own story of spatial data discovery professionally written for the web. I will take you through my own journey of data discovery, provide you with the know-how for accessing large data repositories, demonstrate methods for data harmonizing, processing, modeling and visualizing, and challenge you to think spatially.
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DATA 440 - Special Topics: Data Science Application Capstone
Credits: (1-4)
Selected topics in Data Science. Course is designed to meet the capstone requirement and will focus on Data Application. The topics to be considered will be announced prior to the beginning of the semester. Instructors may require prior approval for registration.
This course may be repeated for credit if topic varies.
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DATA 441 - Advanced Applied Machine Learning
Credits: (3)
Prerequisite(s): DATA 301 (formerly DATA 310) and MATH 211
College Curriculum: COLL 400
This course focuses on creating a compelling story of data discovery where students will develop skills to access, read and analyze disparate data sources from a variety of open-access international, governmental, and private organizational databases and will learn about the challenges associated with real data. To tackle these issues, students will use a variety of advanced analytical and machine learning methods including variable selection, nonparametric regression, functional data analysis and deep learning. Students will communicate their findings through the web by creating a data science paper in HTML format that engages a broad audience to understand the data being addressed, the research methods applied, and the results obtained.
Formerly: DATA 410
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DATA 442 - Neural Networks & Deep Learning
Credits: (3)
Prerequisite(s): DATA 301 (formerly DATA 310) and recommended: (CSCI 241 or ANTH 454 or BIOL 325 or BIOL 327 or ECON 308 or GOVT 302 or MATH 351 or MATH 352 or SOCL 353 )
College Curriculum: COLL 400
This course teaches the foundations of Neural Networks and Deep Learning. Students entering into this course should have, at minimum, a background in data preprocessing, cleaning, manipulation, and dimensionality reduction within python. Through an applied learning project, you will learn how to implement a machine learning project from design to implementation in the context of neural networks. Topics we will cover include the basic building blocks of neural networks, RNNs, convolutional networks and computer vision, backpropagation basics and strategies (including inductive transfer approaches), differences between technical implementations (i.e., TensorFlow, Keras, Torch), and more.
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DATA 443 - Digital Dictatorships
Credits: (4)
Prerequisite(s): CSCI 146 or DATA 201
Dictatorship is one of the oldest forms of government in the world. In recent years, dictators have adapted to shifting political terrain, developing new ways of overcoming threats and maintaining domination. This is particularly the case in the digital sphere where new technologies have profoundly altered how politics operate and peoples interact in both democracies and autocracies alike. This course considers digital dictatorship along two dimensions-as a strategy of autocratic survival (digital tools of control) and as a method of empirical inquiry (“big data” on autocratic politics).
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DATA 444 - Agent-Based Modeling: Simulating Human Development Processes from Neighborhood to Regional Scales
Credits: (4)
Prerequisite(s): DATA 301 (formerly DATA 310) and MATH 112 /MATH 132
College Curriculum: COLL 400
In this course, students will use openly accessible, global, near present-time, high-resolution satellite, household survey and CDR data, with machine learning and spatial statistics methodologies to construct agent-based models of human development processes. Each student will select and describe an administrative subdivision, its demographics, and its built and natural environments in order to estimate social and economic, complex and adapting, agent-based decision, movement and land use models. Students will construct modules that project demand for infrastructure (transportation, water, and electricity) and social services (health care, education, and public safety) as well as simulate an infectious disease outbreak, a natural disaster and unabated urbanization. The programming languages python, java, and R will be used in this course.
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DATA 480 - Special Topics: Non-Computational Capstone
Credits: (3)
Selected topics of a non-computational nature related to Data Science. Course is designed to meet the capstone requirement. The topic to be considered will be announced prior to the beginning of the semester. A student should only be able to take this course a second time if it is covering a separate topic than other times the student has enrolled. Course may count towards other Data Science tracks if approved by the instructor.
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DATA 490 - Independent Research in Data Science
Credits: (1-4)
College Curriculum: COLL 400
This course is designed to permit students with a focus in Data Science to engage in independent research. Working closely with a program faculty member as an advisor, each student will conduct a substantial research project focusing on synthesis and critical analysis, to solve problems in an applied and/or academic setting, to create original material or original scholarship, and to communicate effectively with a diversity of audiences.
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DATA 491 - Mentored Data Science Teaching
Credits: (1)
Prerequisite(s): Student must have achieved an A- or above in the class in which they will assist, or be otherwise approved to enroll. Approval is given by both the instructor and Chair of Department.
A mentored experience in Data Science teaching through selected readings and short discussion sessions. Teaching skills will be developed by assisting in approved Data Science classes.
May be repeated for credit with approval from both instructor and Chair of Department. Formerly: DATA 424
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DATA 495 - Honors - Data Science
Credits: (3)
Students admitted to Senior Honors in Data Science will be responsible for (a) readings and discussion of selected materials; (b) satisfactory completion by April 15 (or November 15 for those on a Spring/Fall Honors schedule) of an original scholarly thesis. DATA 495 and 496 can be used to satisfy the capstone requirement for majors.
Note: For College provisions governing the Admission to Honors, see catalog section titled Honors and Special Programs. For data science requirements, see data science website.
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DATA 496 - Honors - Data Science
Credits: (3)
Students admitted to Senior Honors in Data Science will be responsible for (a) readings and discussion of selected materials; (b) satisfactory completion by April 15 (or November 15 for those on a Spring/Fall Honors schedule) of an original scholarly thesis. DATA 495 and 496 can be used to satisfy the capstone requirement for majors.
Note: For College provisions governing the Admission to Honors, see catalog section titled Honors and Special Programs. For data science requirements, see data science website.
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DATA 498 - Internship
Credits: (1-4)
This course is designed to allow students to gain first-hand knowledge through practical experience in real-world settings. Students will be supervised by and will meet regularly with department faculty members during the course of their internship. Students wishing to receive academic credit for an internship program must request and obtain faculty approval prior to participation in the program. This course is designated as pass/fail only.
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Economics |
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ECON 101 - Principles of Microeconomics
Credits: (3)
Domain (Anchored): CSI
The study of economic behavior at the level of individual households and firms. Topics include scarcity and choice, supply and demand, production, cost and market organization.
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ECON 102 - Principles of Macroeconomics
Credits: (3)
Prerequisite(s): ECON 101
Domain (Anchored): CSI
The study of aggregate economic activity. Topics include national income and output, unemployment, money and inflation, and international trade.
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ECON 150 - First Year Seminar
Credits: (4)
College Curriculum: COLL 150
An exploration of a specific topic in Economics. A grade of C- or better fulfills the COLL 150 requirement. Although topics vary, the courses emphasize academic writing skills, reading and analysis of texts, and discussion.
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ECON 300 - Topics in Economics
Credits: (1-3)
Prerequisite(s): ECON 101 , ECON 102
These variable-credit classes focus on specific topics in economic theory or policy. The topics may differ across sections or vary from semester to semester.
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ECON 303 - Intermediate Microeconomic Theory
Credits: (3)
Prerequisite(s): ECON 101
Domain (Anchored): CSI
The theory of price and resource allocation in a market economy.
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ECON 304 - Intermediate Macroeconomic Theory
Credits: (3)
Prerequisite(s): ECON 102
Domain (Anchored): CSI
Theories of aggregate economic behavior.
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ECON 307 - Principles and Methods of Statistics
Credits: (3)
Prerequisite(s): ECON 101 , ECON 102
College Curriculum: ACTV, MATH
A study of the principles and uses of descriptive statistics, probability distributions, sampling distributions, statistical inference, hypothesis testing and regression analysis. Cannot enroll in Econ 307 after taking or while taking Econ 308. Students may receive credit for only one of the following introductory statistics courses: BUAD 231, ECON 307, and MATH 106.
Note: See section heading “Statistics” under “Requirements for the Baccalaureate Degree.”
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ECON 308 - Econometrics
Credits: (3)
Prerequisite(s): ECON 101 ,ECON 102 , ECON 307 *.
* Students may use BUAD 231, MATH 106, MATH 351, or SOCL 353 in place of ECON 307 as a pre-requisite for ECON 308, but these courses do not count as credit hours toward the Economics major.
A survey of the econometric methods that are commonly used in economic research with emphasis on the application of these techniques rather than their theoretical development. No calculus or linear algebra is required. Cannot enroll in Econ 307 after taking or while taking Econ 308.
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ECON 311 - Money and Banking
Credits: (3)
Prerequisite(s): ECON 101 , ECON 102
An analysis of the monetary system with emphasis upon financial institutions, determination of the money supply and the relationship between money and economic activity.
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ECON 315 - Financial Economics
Credits: (3)
Prerequisite(s): ECON 101 , ECON 102
A survey of the theory and principles of the financial system and of financial economics. Cannot enroll in ECON315 after taking or while taking BUAD323.
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ECON 318 - The Economics of Sports
Credits: (3)
Prerequisite(s): ECON 101 .
In this class students will examine economic issues surrounding the sports industry. The course is organized into three major sections: Industrial Organization, Public Finance, and Labor Markets. We will examine the industrial structure of pro sports by briefly exploring the history of sports leagues and analyzing the impact that the monopoly-like status has on the profitability of teams, player salaries, fan welfare, and the size of subsidies that state and local governments are paying to sports franchises in the form of stadium construction. We will examine the power of franchises to extract subsidies from state and local taxpayers. We will explore the techniques that economists use in determining the economic impact of stadium construction and franchise location on a local and state economy. Questions dealing with player salaries and their impact on the sport will be examined from a number of perspective.
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ECON 321 - Economics of the Public Sector
Credits: (3)
Prerequisite(s): ECON 101 , ECON 102
Theory and principles of public economics with emphasis on state and federal expenditure programs and taxes. Topics include education, welfare, Social Security, unemployment insurance, and the impact of taxes on labor supply, savings, and wealth.
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ECON 322 - Environmental and Natural Resource Economics
Credits: (3)
Prerequisite(s): ECON 101
College Curriculum: COLL 200
Domain (Anchored): CSI
Domain (Reaching Out): NQR
The application of efficiency and equity criteria to environmental issues. Topics include policies for environmental protection, renewable resources, exhaustible resources and unique natural environments.
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ECON 324 - Economics of US Health Policy
Credits: (3)
Prerequisite(s): ECON 101
Economics plays an important role in the design of public policies that address problems in the U.S. healthcare system. Economic theory and analysis can point public policymakers to the underlying causes of problems, help to design policy solutions, and evaluate the effects of implemented policies. This course provides an introduction to the use of economics to address major health policy problems. After a review of the U.S. healthcare system’s general structure and historical development, the course focuses on two major topics: how is healthcare financed, and what drives growth in healthcare spending? In both areas, we will examine economic analysis of past, present, and future public policy to improve financial access to healthcare and lower the rate of growth of healthcare spending.
Cross-listed with: PUBP 324
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ECON 325 - Urban Economics
Credits: (3)
Prerequisite(s): ECON 101
Urban economics uses fundamental economic theory to model location decisions of utility maximizing households and profit maximizing firms. These models are then analyzed to gain a better understanding of why cities exist, what causes cities to grow or shrink, land-use patterns within a city, and the effect of public policy on the health of a city and its populace.
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ECON 331 - Introduction to Mathematical Economics
Credits: (3)
Prerequisite(s): ECON 101 , ECON 102
A survey of mathematical techniques used in economics including topics in linear algebra, calculus and optimization techniques. Emphasis will be on the economic applications of these methods.
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ECON 341 - American Economic History
Credits: (3)
Prerequisite(s): ECON 101 , ECON 102
A study of the major trends and developments in the American economy from colonial times through New Deal. Topics include trade, transportation, business, banking, labor, and policy.
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ECON 342 - Global Economic History
Credits: (3)
Prerequisite(s): ECON 101 , ECON 102
College Curriculum: COLL 200
Domain (Anchored): CSI
Domain (Reaching Out): ALV, NQR
An introduction to the global economic history of the world from ancient times to the mid-20th century, with emphasis on a European development, growth, world-wide economic interactions perspective.
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ECON 344 - African Economic Development
Credits: (3)
Prerequisite(s): ECON 101 and ECON 102
Africa was richer than Asia until the 1970s, but faltered subsequently. We seek credible explanations using economic theory and the available evidence. We will address a number of issues comparatively including the role of geography, demography, historical legacies, the global environment, and domestic economic governance to understand the diversity of economic performance within Africa itself.
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ECON 346 - Comparative Economic Inequality in Multiracial Societies
Credits: (3)
Prerequisite(s): ECON 101 , ECON 102
A comparative study of the historical patterns of inequality of income and wealth in multiracial economies. Theory and empirical evidence on the dynamics of racial and class inequality will be examined with a focus on three case studies (Brazil, South Africa, and the U.S.)
Cross-listed with: AFST 310
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ECON 362 - Regulation of Markets
Credits: (3)
Prerequisite(s): ECON 101 , ECON 102
An analysis of the principles and purposes of government regulation of markets. Topics include the regulatory process, economic and antitrust regulation, environmental regulation, health and safety regulation, and the transportation, telecommunications and public utilities sectors.
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ECON 380 - Experimental Economics
Credits: (3)
Prerequisite(s): ECON 101
Experimental economics is a field in which decision making is examined in a controlled laboratory environment. The resulting data are used to evaluate theories and policies that are not easily tested with naturally occurring data. This course surveys experimental research in many fields including decision and game theory, environmental economics, industrial organization, and public economics, and provides a basic framework for designing and conducting experiments.
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ECON 382 - Comparative Economics
Credits: (3)
Prerequisite(s): ECON 101 , ECON 102
A study of the centrally planned economy as a distinctive system of resource allocation and income distribution. The emphasis is on the economics of transition from classical central planning to a market economy. Case studies of reform include Russia, Hungary, the Czech Republic, Poland and China.
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ECON 384 - Labor Markets and Entrepreneurship
Credits: (3)
Prerequisite(s): ECON 101 and ECON 102
College Curriculum: COLL 350
Significant racial inequality in labor market outcomes and entrepreneurial success persist in open societies. This course examines the nature and extent of the disparities with a focus on three multiracial societies (Brazil, South Africa, and the U.S.). We will address issues of labor market segmentation and discrimination as well as inter-group variations in entrepreneurship with a focus on capital formation, growth, and income inequality.
Cross-listed with: AFST 314
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ECON 385 - Economic Globalization since 1950
Credits: (3)
Prerequisite(s): ECON 101 and ECON 102
An institutionalist perspective on economic globalization since 1950. This period saw two distinct phases of unprecedented economic integration, Pax Americana and the ICT-facilitated globalization of value chains. Course goals include understanding the mechanisms shaping international economic integration, losers and gainers from openness, and the case for new transnational governance and regulatory institutions.
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ECON 398 - Internship
Credits: (1)
Prerequisite(s): ECON 101 and ECON 102 .
A pass/fail, directed readings/research course in conjunction with an internship experience.
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ECON 400 - Topics in Economics
Credits: (3-4)
Prerequisite(s): ECON 303 and/or ECON 304 .
Seminar classes, normally 10-15 junior or senior economics majors, focusing on specific topics in economic theory or policy. Topics vary by section and semester to semester.
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ECON 403 - Advanced Microeconomic Theory: Incentives
Credits: (3)
Prerequisite(s): ECON 303 , MATH 111 or ECON 331 .
An investigation of contracts and other devices that harness self-interest. The aim is to determine the conditions under which the mechanisms generate socially optimal outcomes. Situations in which the pursuit of self-interest is self-defeating, yielding outcomes that are far from socially optimal, are also treated. Calculus is used to identify and evaluate outcomes.
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ECON 407 - Cross Section Econometrics
Credits: (3)
Prerequisite(s): ECON 308 .
Economic data often come as a cross-section of data points, frequently collected as part of a sample survey. The nature of these data calls for the use of a specialized set of tools, which will be developed in the course. Among the models to be examined are discrete, censored and truncated dependent variable, sample selectivity and duration models. Hands-on analysis of data sets will feature prominently.
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ECON 408 - Time-Series Econometrics
Credits: (3)
Prerequisite(s): ECON 308 , ECON 331 (or MATH 211 ).
This course is an introduction to the econometric analysis of time series data. Topics include ARIMA models, forecasting, analysis of nonstationary series, unit root tests, co-integration and principles of modeling.
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ECON 409 - Research Methods in Experimental Economics
Credits: (3)
Prerequisite(s): ECON 380
College Curriculum: COLL 400
In the first half of the semester students work together to design and conduct human subject experiments that address research questions motivated by prior coursework in economics. In the second half of the semester students analyze the resulting data and work independently to prepare manuscripts. Students meet regularly during the data analysis and writing phase of the course to make progress reports on their manuscripts and to discuss any challenges they face with their research. Students also exchange rough drafts of papers and provide written feedback to each other. At the end of the semester all research subjects are invited to attend a seminar in which students present the findings from their research papers.
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ECON 410 - Game Theory
Credits: (3)
Prerequisite(s): ECON 101 and ECON 303 .
Game Theory is a set of mathematical models used to study how individuals make decisions when their actions affect each other. The emphasis of the course material is a mix of formal theory and applications, including bargaining, information and auctions. While economists turn to game theory to model many situations, the field is firmly rooted in mathematics. Thus, you will struggle in this course if you are not very comfortable with college-level algebra and basic calculus. In addition to mathematical modeling, this course will make extensive use of economics experiments to identify situations where game theory predicts actual behavior and to learn more about why game theory fails to predict behavior in some settings.
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ECON 411 - Advanced Macroeconomic
Credits: (3)
Prerequisite(s): ECON 304 , MATH 111 .
A critical survey of the current state of macroeconomic model building including discussions of Neoclassical and New Keynesian models, emphasizing the microeconomic foundations of the models and their implications for business cycle analysis.
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ECON 412 - Empirical Microeconomics
Credits: (3)
Prerequisite(s): ECON 308
College Curriculum: COLL 400
Equips students with a set of conceptual and econometric skills to estimate the causal impact of one factor on some outcome of interest. Methods include randomized control trials, natural experiments, instrumental variables, difference-in-differences, matching, regression discontinuity, and synthetic control. Examples explore the causal effect of policies, laws, programs and “natural experiments,” primarily drawn from development, public, and labor economics. Students apply these methods to their own research design and present this design and their findings at the semester’s conclusion.
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ECON 413 - Dynamic Stochastic General Equilibrium Modeling
Credits: (3)
Prerequisite(s): (CSCI 141 and ECON 303 and ECON 304 and MATH 112 )
College Curriculum: COLL 400
This course combines calculus, statistics, economic theory, and programming to answer macroeconomic questions. Macroeconomic models range from the reduced-form to the structural. This course familiarizes students with vector autoregressions that are useful for establishing facts from data. We will then explore the application of dynamic stochastic general equilibrium (DSGE) models, which are the workshorse models of central banks and other macroeconomic policy institutions, to understand those facts.
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ECON 414 - Bayesian Econometrics
Credits: (3)
Prerequisite(s): ECON 308
College Curriculum: COLL 400
This course examines the use of Bayesian estimation methods for a wide variety of settings in applied economics. After a brief primer on Bayesian statistics, we will examine the use of the Metropolis-Hastings algorithm for parameter estimation via Markov Chain Monte Carlo methods. We will explore heirarchical models (such as mixed regression), multivariate probit, and time series models and apply these to a variety of policy and scientific questions. A significant focus of the course will be the communicating the degree of scientific knowledge and uncertainty in a variety of settings including Oped’s, blog posts, and scientific notebooks which will be targeted to a variety of audiences.
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ECON 415 - Applied Financial Derivatives
Credits: (3)
Prerequisite(s): ECON 303 and ECON 307 .
The economic theory of stochastic calculus and the solutions of the resulting partial differential equations are developed in the context of equity derivatives. Corollary risk-management characteristics are considered. Context is provided as each student manages a paper portfolio of electronic derivatives.
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ECON 416 - Capital Markets and Portfolio Choices
Credits: (3)
Prerequisite(s): ECON 303 and ECON 304 and ECON 308
College Curriculum: COLL 400
This course is focused on studying financial assets and the capital markets in which they are traded. The course belongs to the larger field of financial economics. It will provide analytical tools and derive formal models in asset pricing. The set of tools is used to understand how different assets are priced in the market and the relationship between risk and return. This course is meant to train students to think in a structured, analytical rigorous way about the fundamentals of asset pricing models, starting from the notions of market efficiency and ending with risk management principles. The course emphasizes case studies, group work, and interactive class discussions. Finally, this course will help prepare students entering graduate education or starting careers in management, finance, or economic consulting.
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ECON 420 - Economics of Information
Credits: (3)
Prerequisite(s): ECON 303 .
How markets and governments create incentives to elicit private information from individuals and firms, and how individual welfare is affected as a result. Topics include: Auctions; bank failures; internet commerce; education; mandatory retirement; voting and preference revelation; allocating dormitory rooms.
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ECON 422 - Applied Environmental Economics
Credits: (3)
Prerequisite(s): MATH 111 , ECON 308 .
This course will cover the application of welfare economics to environmental problems. Topics include differences in consumer surplus and other measures of economic welfare and techniques to measure the economic value of environmental resources. The course will be organized around contemporary environmental issues; for example, the economic value of oyster reef restoration in the Chesapeake Bay, preservation of endangered species, and impacts of global climate change on property. The course will examine these problems using real world data and will expose students to a wide variety of economic valuation techniques.
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