STATISTICAL INFERENCE
Prerequisites: STAT GR5203 or the equivalent, and two semesters of calculus. Calculus-based introduction to the theory of statistics. Useful distributions, law of large numbers and central limit theorem, point estimation, hypothesis testing, confidence intervals, maximum likelihood, likelihood ratio tests, nonparametric procedures, theory of least squares and analysis of variance.
- Department: Statistics
- MW 8:40 a.m.-11:25 a.m.
- MW 1:10 p.m.-3:40 p.m.
- MW 6:10 p.m.-8:40 p.m.
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Instructor:
Regina Dolgoarshinnykh
CULPA: 2 Info -
Instructor:
Michael Sobel
CULPA: 5 Wikipedia h-index: 35 Info -
Instructor:
Bodhisattva Sen
h-index: 24 Info - 3 points
APPLIED ANALYTICS FRAMEWORKS & METHDS II
APP AN FRAMEWORKS & METHODS II
- Department: Applied Analytics
- M 6:10 p.m.-8 p.m.
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Instructor:
David Shilane
Info - 3 points
APPLIED ANALYTICS FRAMEWORKS & METHDS II
APAN FRMWRKS & MTHDS II ONLINE
- Department: Applied Analytics
- T 8:10 p.m.-10 p.m.
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Instructor:
Gurgen Hayrapetyan
Info - 3 points
NARRATIVE ETHICS
- Department: Narrative Medicine
- T 6:10 p.m.-8 p.m.
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Instructor:
Danielle R Spencer
h-index: 5 Info - 3 points
LINEAR REGRESSION MODELS
Prerequisites: STAT GR5203 and GR5204 or the equivalent. Theory and practice of regression analysis, Simple and multiple regression, including testing, estimation, and confidence procedures, modeling, regression diagnostics and plots, polynomial regression, colinearity and confounding, model selection, geometry of least squares. Extensive use of the computer to analyse data.
- Department: Statistics
- TR 2:40 p.m.-3:55 p.m.
- MW 1:10 p.m.-2:25 p.m.
- TR 6:10 p.m.-7:25 p.m.
- MW 8:40 a.m.-9:55 a.m.
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Instructor:
Philip Protter
h-index: 50 Info -
Instructor:
Banu Baydil
CULPA: 10
Info
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Instructor:
Alex Pijyan
Info -
Instructor:
Yuqi Gu
h-index: 6 Info - 3 points
GEOGRAPHIC INFORMATIONS SYSTEMS (GIS) FO
GEOGRAPHIC INFORMATION SYSTEMS
- Department: Sustainability Management
- W 6:10 p.m.-8 p.m.
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Instructor:
Fabien Cottier
Info - 3 points
STAT COMP & INTRO DATA SCIENCE
STAT COMP & INTRO TO DATA SCI
Corequisites: STAT GR5204 and GR5205 or the equivalent. Introduction to programming in the R statistical package: functions, objects, data structures, flow control, input and output, debugging, logical design, and abstraction. Writing code for numerical and graphical statistical analyses. Writing maintainable code and testing, stochastic simulations, paralleizing data analyses, and working with large data sets. Examples from data science will be used for demonstration.
STAT COMP & INTRO DATA SCIENCE
Corequisites: STAT GR5204 and GR5205 or the equivalent. Introduction to programming in the R statistical package: functions, objects, data structures, flow control, input and output, debugging, logical design, and abstraction. Writing code for numerical and graphical statistical analyses. Writing maintainable code and testing, stochastic simulations, paralleizing data analyses, and working with large data sets. Examples from data science will be used for demonstration.
- Department: Statistics
- F 10:10 a.m.-12:40 p.m.
- F 6:10 p.m.-8:40 p.m.
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Instructor:
Yongchan Kwon
Info -
Instructor:
Haiyuan Wang
Info - 3 points
ADVANCED MEDIATION
On a daily basis we may encounter conflicts and seek to resolve them through negotiations and other forms of conflict resolution. Some of these are simple and easy to resolve, while others are complex and may require the support of a third party, or
mediator
. In this course we will explore mediation from several points of view and approaches. We will build on what you have learned in Introduction to Mediation (PS5107) both conceptually as you expand your knowledge of the field and practically as you further develop your skills as mediators. This course will be a blend of theory and practice. As adult learners you will be expected to situate this learning and development within your own current status as third party interveners or mediators.
- Department: Negotiation & Conflict Resolution
- USSU 9 a.m.-2 p.m.
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Instructor:
Stephanie S Chow
Info - 3 points
ELEMENTARY STOCHASTIC PROCESSE
Corequisites: GR5203 or the equivalent. Review of elements of probability theory. Poisson processes. Renewal theory. Walds equation. Introduction to discrete and continuous time Markov chains. Applications to queueing theory, inventory models, branching processes.
- Department: Statistics
- MW 11:40 a.m.-12:55 p.m.
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Instructor:
Richard Davis
CULPA: 3 h-index: 60 Info - 3 points
PYTHON FOR DATA ANALYSIS
- Department: Applied Analytics
- W 6:10 p.m.-8 p.m.
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Instructor:
Guilherme de Oliveira
Info - 3 points
PYTHON FOR DATA ANALYSIS
PYTHON FOR DATA ANALYSIS ONLNE
- Department: Applied Analytics
- W 8:10 p.m.-10 p.m.
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Instructor:
Max Vilenchik
Info - 3 points
DIRECTING I
Students explore the grammatical rules and narrative elements of cinematic storytelling by completing a minimum of three short, nondialogue exercises and two sound exercises, all shot and edited in video. Emphasizes using the camera as an articulate narrator to tell a coherent, grammatically correct, engaging, and cinematic story. Technical workshops on camera, lighting, sound, and editing accompany the workshops, as well as lectures that provide a methodology for the director.
- Department: Film
- R 2 p.m.-5 p.m.
- W 9:30 a.m.-12:30 p.m.
- R 2 p.m.-5 p.m.
- T 2 p.m.-5 p.m.
- R 2 p.m.-5 p.m.
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Instructor:
Hilary Brougher
Wikipedia Info -
Instructor:
Anocha Suwichakornpong
Wikipedia Info -
Instructor:
Ramin Bahrani
Wikipedia Info -
Instructor:
Diana Peralta
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Instructor:
Bette Gordon
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Instructor:
Bogdan G Apetri
Info - 3 points
CONFLICT RESOLUTION AND DYNAMICAL SYSTEM
CONF RESOLUTION/DYNAMIC S
Dynamical Systems Theory (DST) is a methodology developed in the hard sciences to understand complex systems—from the weather to the functioning of cells, using mathematical algorithms. We added the lens of social-psychological concepts and practices to better understand how to apply DST to conflict. We are now applying DST to conflict analysis and resolution for larger social problems and conflicts that are protracted, deeply embedded and have multiple complex issues. This DST approach goes beyond linear problem-solving and embraces complexity in new ways. Dynamical Systems and Conflict Resolution (NECR 5210) is a required 3-credit course in the Negotiation and Conflict Resolution Program (NECR). Students are expected to spend on average 20 hours per week on this course, including media, group work, readings, and other assignments. NECR 5210 builds on concepts from Understanding Conflict and Cooperation (NECR 5101), where students became familiar with conflict resolution frames, theories, and models, as well as a basic understanding of the DST approach. This course will further develop and advance student understanding and use of advanced DST concepts and tools that will be useful for scholar-practitioners facing situations that require a systemic approach for more highly complex conflicts. It is a complementary approach that rounds out the other concepts and skills student learn in the program. Throughout this course students will work individually and in groups on multiple case studies, to understand and apply DST methodology, while developing an appreciation for the more fluid and non-linear DST approach.
- Department: Negotiation & Conflict Resolution
- 3 points
ENV SUST INDICATORS: CONSTRUCTION & USE
CONSTRUCTION AND USE
This course will present students with the architecture, data, methods, and use cases of environmental indicators, from national-level indices to spatial indices. The course will draw on the instructor’s experience in developing environmental sustainability, vulnerability and risk indicators for the Yale/Columbia EPI as well as for a diverse range of clients including the Global Environmental Facility, UN Environment, and the US Agency for International Development. Guest lecturers will provide exposure to Lamont experience in monitoring the ecological and health impacts of environmental pollution and the use of environmental indicators in New York City government. Beyond lecture and discussion, classroom activities will include learning games, role play and case study methods. The course will explore alternative framings of sustainability, vulnerability and performance, as well as design approaches and aggregation techniques for creating composite indicators (e.g., hierarchical approaches vs. data reduction methods such as principal components analysis). The course will examine data sources from both in-situ monitoring and satellite remote sensing, and issues with their evaluation and appropriateness for use cases and end users. In lab sessions, the students will use pre-packaged data and basic statistical packages to understand the factors that influence index and ranking results, and will construct their own simple comparative index for a thematic area and region or country of their choice. They will learn to critically assess existing indicators and indices, and to construct their own. In addition, students will assess the impacts of environmental performance in several developing and developed countries using available data (e.g., pollutant levels in soils and air in Beijing and NYC), and project future changes based on the trends they see in their assessments. The course will also examine theories that describe the role of scientific information in decision-making processes, and factors that influence the uptake of information in those processes. The course will present best practices for designing effective indicators that can drive policy decisions.
Advising Note:
Students are required to have had prior coursework in descriptive and inferential statistics, and knowledge of at least one statistical package, R or Python is preferred.
- Department: Sustainability Technology
- M 6:10 p.m.-8 p.m.
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Instructor:
Alexander M Desherbinin
Info - 3 points
MICROECONOMICS ANALYSIS I
- Department: Economics
- MW 8:40 a.m.-9:55 a.m.
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Instructor:
Bernard Salanie
CULPA: 18 Wikipedia h-index: 40 Info - 3 points
CONFLICT, SOCIAL NETWORKS AND COMMUNICAT
CONFL SOCIAL NETWKS/COMM
- Department: Auditing
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Instructor:
Ted Perlmutter
Info - 0 points
CONFLICT, SOCIAL NETWORKS AND COMMUNICAT
CONFL SOCIAL NETWKS/COMM
- Department: Negotiation & Conflict Resolution
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Instructor:
Ted Perlmutter
Info - 3 points
MACROECONOMICS ANALYSIS I
- Department: Economics
- R 6:10 p.m.-8 p.m.
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Instructor:
Julian Di Giovanni
Info - 3 points
ADVANCED MICROECONOMICS
- Department: Economics
- M 4:10 p.m.-6 p.m.
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Instructor:
Humberto L Moreira
Info - 3 points
ADVANCED MACROECONOMICS
- Department: Economics
- W 2:10 p.m.-4 p.m.
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Instructor:
Irasema Alonso
CULPA: 12 Info - 3 points
QUANT MTHDS IN INVESTMENT MGMT
Prerequisites: Knowledge of statistics basics and programming skills in any programming language. Surveys the field of quantitative investment strategies from a buy side perspective, through the eyes of portfolio managers, analysts and investors. Financial modeling there often involves avoiding complexity in favor of simplicity and practical compromise. All necessary material scattered in finance, computer science and statistics is combined into a project-based curriculum, which give students hands-on experience to solve real world problems in portfolio management. Students will work with market and historical data to develop and test trading and risk management strategies. Programming projects are required to complete this course.
- Department: Mathematics
- T 7:40 p.m.-10 p.m.
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Instructor:
Alberto Botter
Info - 3 points
FOUNDATIONS OF SPORTS MANAGEMENT
FOUNDATIONS OF SPORTS MGMT
- Department: Sports Management
- W 12:10 p.m.-2 p.m.
- M 6:10 p.m.-8 p.m.
- T 6:10 p.m.-8 p.m.
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Instructor:
Scott Rosner
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Instructor:
Christopher Lencheski
Info -
Instructor:
Michael Dittelman
Info - 3 points
TIME SERIES ANALYSIS
Prerequisites: STAT GR5205 Least squares smoothing and prediction, linear systems, Fourier analysis, and spectral estimation. Impulse response and transfer function. Fourier series, the fast Fourier transform, autocorrelation function, and spectral density. Univariate Box-Jenkins modeling and forecasting. Emphasis on applications. Examples from the physical sciences, social sciences, and business. Computing is an integral part of the course.
- Department: Statistics
- MW 2:40 p.m.-3:55 p.m.
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Instructor:
Rongning Wu
CULPA: 1 Info - 3 points
Forms and Practices of Islamic Knowledge
Form/Prctice Islamic Know
The course is an introduction to the disciplines, institutions, and practices of knowledge in premodern Islam. We will start by examining the concept of knowledge in the Qur’an, Hadith and early traditions, and the categories and hierarchies of scholarly disciplines that evolved over the centuries, with attention to traditional discussions about their legitimacy, function and methodology. We will survey representative texts on pedagogy and instruction, and learn about sites of learning, libraries, curriculum, and the ethics of learning. We will study the techniques of textual composition, transmission and preservation. We will explore practices of reading and writing. We will seek to understand the role of women scholars, and reflect on the relation between knowledge, society and technology. Our main focus will be on developments and innovations in the post-formative period, roughly after 1200 CE. Students will be asked to read relevant materials (in Arabic and English) and to discuss the material each week. A final paper is due on the last day of the seminar. The course includes a visit to the Columbia University Rare Book & Manuscript Library to view materials relevant to the themes covered in this course.
- Department: Middle Eastern, South Asian and African Studies
- M 4:10 p.m.-6 p.m.
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Instructor:
Islam Dayeh
Info - 4 points
BAYESIAN STATISTICS
This course introduces the Bayesian paradigm for statistical inference. Topics covered include prior and posterior distributions: conjugate priors, informative and non-informative priors; one- and two-sample problems; models for normal data, models for binary data, Bayesian linear models, Bayesian computation: MCMC algorithms, the Gibbs sampler; hierarchical models; hypothesis testing, Bayes factors, model selection; use of statistical software. Prerequisites: A course in the theory of statistical inference, such as STAT GU4204/GR5204 a course in statistical modeling and data analysis such as STAT GU4205/GR5205.
- Department: Statistics
- MW 6:10 p.m.-7:25 p.m.
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Instructor:
Ronald Neath
CULPA: 13
Info
- 3 points
DIRECTING ACTORS I
A workshop in which the student explores the craft and vocabulary of the actor through exercises and scene study as actors and the incorporation of the actor's vocabulary in directed scenes. Exploration of script analysis, casting, and the rehearsal process.
- Department: Film
- T 2 p.m.-5 p.m.
- M 2 p.m.-5 p.m.
- T 2 p.m.-5 p.m.
- M 2 p.m.-5 p.m.
- T 6 p.m.-9 p.m.
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Instructor:
Benjamin K Martin
CULPA: 2 Info -
Instructor:
Anna Maria Cianciulli
Info -
Instructor:
Jodie Markell
Wikipedia Info -
Instructor:
Adrienne Weiss
Info -
Instructor:
John Rubin
Info -
Instructor:
Mikael Sodersten
Info - 3 points
CHANGE MANAGEMENT
Change is a necessary and constant part of any organization. The change may be expected, or it may be in reaction to unanticipated external and/or internal factors. In fact, organizations that do not change do not last. Change initiatives can be exceedingly complex and disorienting, however. The success of a given changeinitiative often rests on the clarity of vision of an organization’s leaders; an accurate and sensitiveunderstanding of the organization’s culture; the involvement, input and buy-in of multiple internal andexternal stakeholders to the change objectives and process; leaders’ ability to leverage technology tocommunicate and drive change; and an organization’s analytical capabilities to document and measureprogress, and continue to iterate and improve. In light of these requirements, this course seeks to ask: What is the role of the HCM leader in facilitatingchange within an organization? The aims of this course are not abstract. This course will help studentsdevelop skills to support actual organizations (their own and/or others) through change. Lectures, readings,videos, in-class and asynchronous discussions, and assignments will all focus on the practical application ofchange theory and empirical research to real-world organizational contexts. This course is an advanced elective within the Master of Science in Human Capital Management program.Prerequisites include “HCMPS5100: Introduction to Human Capital Management,” and “HCMPS5150:Integrated Talent Management Strategies.” Some familiarity with people analytics and digital approaches toHuman Capital Management will also be helpful.
- Department: Human Capital Management
- T 6:10 p.m.-8 p.m.
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Instructor:
Lee Miller
Wikipedia Info - 3 points
ADVOCACY & ORGANIZING
Our interpersonal experiences and the personal identities we hold both shape and contribute to our individual concepts of health, as well as to our awareness of the beliefs and identities held by others. This course examines how various marginalized groups have historically organized and advocated to bring about change in communities impacted by health disparities and social injustice. How can understanding their stories and the strategies they've implemented to construct, share, and collect their narratives, inform health professionals and their allies in developing new and innovative approaches to hear, interpret, and respond to the needs of the communities they are charged with serving? At a time when a renewed focus is being placed on health equity, social justice, race, bias, resource distribution, and access, it is imperative to look more closely at the experiences of communities and the individuals within them who have been placed at greater vulnerability. With an attentiveness to intersectionality, critical race theory, and media studies, course materials will guide an exploration of narrative and its relationship to activism, advocacy, and messaging around community health.
- Department: Narrative Medicine
- R 1:10 p.m.-3 p.m.
- 3 points
INNOVATIONS IN PHILANTHROPY
- Department: Non Profit Management
- T 6:10 p.m.-8 p.m.
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Instructor:
Richard T Feiner
Info - 3 points
INNOVATIONS IN PHILANTHROPY
- Department: Auditing
- T 6:10 p.m.-8 p.m.
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Instructor:
Richard T Feiner
Info - 0 points
ATHLETE ACTIVISM & SOCL JUSTICE IN SPRTS
- Department: Sports Management
- M 2:10 p.m.-4 p.m.
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Instructor:
Leonard Elmore
Info - 3 points
THE EARTH'S CLIMATE SYSTEM
- Department: Sustainability Management
- T 4:10 p.m.-6 p.m.
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Instructor:
Benjamin I Cook
CULPA: 3 h-index: 56 Info - 3 points
DIVERSITY, EQUITY & INCLUSION IN PHILANT
DIV, EQUITY & INCLUSN IN
Diversity, equity, and inclusion (DEI) is an increasingly salient practice in the charitable sector. Done well, DEI practice – such as more diverse recruitment policies, more inclusive organizational culture, and greater attention to the equitable distribution of programmatic outcomes – helps nonprofit and foundation managers and leaders attract and retain talent, improve programmatic outcomes, and lend greater credibility to the work of the charitable sector. The need for such practice is evident: most nonprofits and foundations are not representative of the communities they serve; the accumulation of wealth that enables large private foundations to exist exacerbates the very issues they may seek to combat; and in seeking to help those affected by inequality, nonprofits and foundations may reproduce the same patterns of inequality within their own organizations. Despite the growing need for effective DEI practice, much of the knowledge of it is diffuse and disconnected. At times, practitioners can’t even agree on the basic terms. Yet in this disagreement lies a clue: pursued deeply, a DEI analysis leads one to conclude that mainstream institutions, and the broader society of which they are a part, are ultimately designed to make DEI difficult to understand, much less enact. This means that DEI practice eventually names and pushes back on the very power relations and institutional dynamics that surround us in the charitable sector and make our work possible. To reckon fully with DEI means to question the very assumptions and relationships on which our sector is based. This course aims to equip students with critical faculties and practical tools to be informed and ethical practitioners of DEI in the charitable sector while remaining alive to the tensions between DEI and current sector practice.
- Department: Non Profit Management
- M 6:30 p.m.-8 p.m.
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Instructor:
Vernetta L Walker
Info - 3 points
ADVANCED MACHINE LEARNING
Prerequisites: STAT GR5241 This course covers some advanced topics in machine learning and has an emphasis on applications to real world data. A major part of this course is a course project which consists of an in-class presentation and a written project report.
- Department: Statistics
- TR 10:10 a.m.-11:25 a.m.
- TR 11:40 a.m.-12:55 p.m.
- 3 points
APPLIED DATA SCIENCE
Prerequisites: Pre-requisite for this course includes working knowledge in Statistics and Probability, data mining, statistical modeling and machine learning. Prior programming experience in R or Python is required. This course will incorporate knowledge and skills covered in a statistical curriculum with topics and projects in data science. Programming will covered using existing tools in R. Computing best practices will be taught using test-driven development, version control, and collaboration. Students finish the class with a portfolio of projects, and deeper understanding of several core statistical/machine-learning algorithms. Short project cycles throughout the semester provide students extensive hands-on experience with various data-driven applications.
- Department: Statistics
- W 6:10 p.m.-8:55 p.m.
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Instructor:
Ying Liu
CULPA: 2 h-index: 12 Info - 3 points
Introduction to TensorFlow with Python
Intro. TensorFlow with Py
This course is an optional companion lab course for GR5242 Advanced Machine Learning. The aim of this course is to help students acquire the basic computational skills in Tensorflow and Python to implement machine learning models. Lab class materials will be aligned closely with the topics covered in GR5242. Google Colab and Jupyter notebooks will be used as the main tools for the hands-on lab exercises. Open to GR5242 students only.
Prerequisites
Some familiarity with python is assumed, but we will begin the class with a tutorial on 'Python for machine learning'.
- Department: Statistics
- R 5:35 p.m.-6:35 p.m.
- R 6:45 p.m.-7:45 p.m.
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Instructor:
Ka-Yi Ng
Info - 1 points
EXTERNAL STAKEHOLDER REQUIREMENTS
- Department: Enterprise Risk Management
- W 6:10 p.m.-8 p.m.
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Instructor:
Jean Michel Ngalikpima
Info - 3 points
EXTERNAL STAKEHOLDER REQUIREMENTS
EXT STAKEHOLDER REQ (ONLINE)
- Department: Enterprise Risk Management
- M 6:10 p.m.-8 p.m.
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Instructor:
Alan Cheung
h-index: 5 Info - 3 points
FUNDAMENTALS OF EDITING
This online class explores the creative and narrative principals of editing through the editing of students' 8-12 minute films and / or other footage. Instructors are professional editors who will provide lecture and individual based instruction.
- Department: Film
- W 6 p.m.-9 p.m.
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Instructor:
John D Allen
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Instructor:
Andrew Hafitz
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Instructor:
David G Gutnik
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Instructor:
Madeleine Gavin
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Instructor:
Susan Korda
Info - 1.5 points
THE ART AND CRAFT OF PRACTICE
NECR FIELDWORK
The required “The Art and Craft of Practice
”
course is designed to introduce students to key practical insights, tips, and professional skills necessary for any successful conflict resolution practitioner. In this course, students will be required to practically apply some of the tools and techniques of NECR, and appreciate the importance of combining and reformulating the basic NECR concepts in order to serve their exact needs in the field. Through this course, students have the opportunity to apply what they have learned in the classroom, learn additional practical research skills, and adjust them to their own very specific professional aspirations in the field. This course also helps students strategize their next professional steps in the field in a concise, methodical way. It is important to keep in mind that the Conflict Resolution field at large is quite diverse, and our students have unique backgrounds and future aspirations. Therefore, this course is customized in coordination with each student during 1-on-1 sessions that take place at the beginning of the semester, in order for each student to be working on something that is clear, and has practical value for his/her very specific professional interests. As with many things in life, proactiveness, creativity, and an entrepreneurial spirit are keys to success for our very challenging field. Each student will be having a required 1-on-1 session with the instructor, where the instructor will help the student explore ways to creatively strategize their next professional steps as practitioners and also develop the instructions for the final paper that match the needs of the student. Overall, the goal is to provide students with an enriching, personal experience that helps them rethink their role as practitioners and strategize better their short/ long term goals in Negotiation and Conflict Resolution.
- Department: Negotiation & Conflict Resolution
- U 9 a.m.-11:30 a.m.
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Instructor:
Nikolas Katsimpras
Info - 1 points
DATA ANALYTICS/METRICS IN THE NONPROFIT
Data Analytics
- Department: Non Profit Management
- T 6:10 p.m.-8 p.m.
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Instructor:
Jessie H Lee
Info - 3 points
DATA ANALYTICS/METRICS IN THE NONPROFIT
DATA ANLTCS/METRICS IN NONPRFT
Data Analytics
- Department: Non Profit Management
- W 6:30 p.m.-8 p.m.
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Instructor:
James W Lauckhardt
Info - 3 points
BUILDING RESILIENCE IN 21ST CENTURY DETR
BLDG RESILIENCE IN DETROI
Detroit is well-recognized as the Blackest big city in America within one of the most segregated metropolitan areas. This preeminence collapsed over the span of the past 40 years under the weight of racist public policy, public and private malfeasance, financial disinvestment, and the temporary usurpation of Black political power. In an effort to better understand current conflicts between Black citizens and their government, this class will examine the role of race in public policy formation, institutional systems, and government. We will examine the thesis that sustainability and racism cannot co-exist; that sustainability is rooted in inclusive social well-being now and in future generations, whereas racism is rooted in hoarding of power and resources for one dominant group. We will explore grass-roots efforts to address root causes, community development efforts to build sustainable communities, and alternative approaches to restructuring local economies.
- Department: Sustainability Management
- W 6:10 p.m.-8 p.m.
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Instructor:
Donna Givens Davidson
Info - 3 points
DATA ANALYSIS AND VISUALIZATION IN SUSTA
DATA ANALYSIS & VIS SUST
- Department: Sustainability Management
- T 6:10 p.m.-8 p.m.
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Instructor:
Gregory G Yetman
Info - 3 points
VALUE OF BRAND
VALUE OF BRAND:MAKNG-BUSI
This course introduces students to the economic importance of brand building activities based on the proven link between brand equity and business performance. Students examine the role that strategy and communication play in building brand equity, and explore how the changing media landscape is causing companies to rethink traditional brand-building practices. Students will use critical thinking, case-analysis, market research, and strategic presentations to persuade a business decision maker to invest in brand building efforts. For students who are interested in building stronger brand cultures within their organizations (for both the profit and nonprofit sectors) and/or for pursuing careers on the brand side of strategy, this course answers the question: Why should businesses and institutions care about branding?
- Department: Auditing
- W 8:10 p.m.-10 p.m.
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Instructor:
Kristen J Campolattaro
Info - 0 points
VALUE OF BRAND
This course introduces students to the economic importance of brand building activities based on the proven link between brand equity and business performance. Students examine the role that strategy and communication play in building brand equity, and explore how the changing media landscape is causing companies to rethink traditional brand-building practices. Students will use critical thinking, case-analysis, market research, and strategic presentations to persuade a business decision maker to invest in brand building efforts. For students who are interested in building stronger brand cultures within their organizations (for both the profit and nonprofit sectors) and/or for pursuing careers on the brand side of strategy, this course answers the question: Why should businesses and institutions care about branding?
- Department: Strategic Communication
- W 8:10 p.m.-10 p.m.
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Instructor:
Kristen J Campolattaro
Info - 3 points
ORGANIZATIONAL STRATEGY AND LEARNING
ORG STRAT AND LEARNING
- Department: Human Capital Management
- M 6:10 p.m.-8 p.m.
- M 8:30 p.m.-10 p.m.
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Instructor:
Nabeel Ahmad
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Instructor:
Sara Daly-Padron
Info - 3 points
CORPORATE, PRIVATE, COMMUNTY FOUNDATIONS
- Department: Auditing
- M 6:30 p.m.-8 p.m.
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Instructor:
John Tyler
h-index: 3 Info - 0 points
CORPORATE, PRIVATE, COMMUNTY FOUNDATIONS
CORP PRIV COMM FOUNDATIONS
- Department: Non Profit Management
- M 6:30 p.m.-8 p.m.
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Instructor:
John Tyler
h-index: 3 Info - 3 points
STATISTICAL METHODS IN FINANCE
Prerequisites: STAT GR5204 or the equivalent. STAT GR5205 is recommended. A fast-paced introduction to statistical methods used in quantitative finance. Financial applications and statistical methodologies are intertwined in all lectures. Topics include regression analysis and applications to the Capital Asset Pricing Model and multifactor pricing models, principal components and multivariate analysis, smoothing techniques and estimation of yield curves statistical methods for financial time series, value at risk, term structure models and fixed income research, and estimation and modeling of volatilities. Hands-on experience with financial data.
- Department: Statistics
- S 10:10 a.m.-12:40 p.m.
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Instructor:
Zhiliang Ying
CULPA: 1 Wikipedia h-index: 62 Info - 3 points
STAT INF/TIME-SERIES MODELLING
Prerequisites: STAT GR5205 or the equivalent. Available to SSP, SMP Modeling and inference for random processes, from natural sciences to finance and economics. ARMA, ARCH, GARCH and nonlinear models, parameter estimation, prediction and filtering.
- Department: Statistics
- TR 6:10 p.m.-7:25 p.m.
- S 10:10 a.m.-12:40 p.m.
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Instructor:
Gokce Dayanikli
Info -
Instructor:
Franz Rembart
Info - 3 points
STOCHASTC PROCSSES-APPLICTNS I
Prerequisites: STAT GR5203 or the equivalent. Basics of continuous-time stochastic processes. Wiener processes. Stochastic integrals. Ito's formula, stochastic calculus. Stochastic exponentials and Girsanov's theorem. Gaussian processes. Stochastic differential equations. Additional topics as time permits.
- Department: Statistics
- MW 4:10 p.m.-5:25 p.m.
- MW 6:10 p.m.-7:25 p.m.
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Instructor:
Ioannis Karatzas
CULPA: 7 h-index: 58 Info -
Instructor:
Lars T Nielsen
h-index: 17 Info - 3 points
MANAGING THE MISSION-BASED ORGANIZATION
- Department: Non Profit Management
- M 6:30 p.m.-8 p.m.
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Instructor:
Timothy Higdon
Info - 3 points
TRANSFORMING TOTAL REWARDS
- Department: Human Capital Management
- W 6:10 p.m.-8 p.m.
- W 6:30 p.m.-8 p.m.
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Instructor:
Hassan Abdulhaqq
Info -
Instructor:
Edna B Chun
Info -
Instructor:
Solange Charas
h-index: 4 Info - 3 points
MANAGING DIVERGING STAKEHOLDER INTERESTS
RESPONSE TO CLIMATE CHANG
This course will explore ways in which a changing climate drives divergent, often conflicting, responses from different segments of society: distinct economic classes, industries, communities, countries, etc. This course takes a case study approach, looking at how specific socio-economic impacts of global warming are changing alignments and/or deepening stakeholder entrenchment. It has become common to say that “society lacks political will” to implement effective climate policy; but a closer look indicates that it might be more accurate to say that strong, but conflicting, interests delay action. Further, when the costs of climate change and other environmental risks accrue to one social group while the benefits of new opportunities to another, regulatory policy can be badly distorted. To address this set of problems students will start with science-based projections of change in the Arctic and North America, and will look at how different stakeholders have already responded to change. The course will include a segment on modeling stakeholder conflict. Several types of models will be described and students will have access to a version of the Human and Nature Dynamics (HANDY) model that has been modified to include delays in policy implementation. The HANDY model runs quickly enough to try out scenarios in class to test possible impacts of conflict and delay on environmental sustainability.
- Department: Sustainability Technology
- M 4:10 p.m.-6 p.m.
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Instructor:
Robert Newton
h-index: 9 Info - 3 points
CAPITAL MARKETS & INVESTMENTS
Risk/return tradeoff, diversification and their role in the modern portfolio theory, their consequences for asset allocation, portfilio optimization. Capitol Asset Pricing Model, Modern Portfolio Theory, Factor Models, Equities Valuation, definition and treatment of futures, options and fixed income securities will be covered.
- Department: Mathematics
- S 7 p.m.-9:20 p.m.
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Instructor:
Alexei Chekhlov
CULPA: 3
h-index: 10
Info
- 3 points
ROLE & UNIQUE NATURE OF NONPROFIT SECTOR
ROLE & UNIQUE NATURE OF NONPRF
- Department: Non Profit Management
- W 2:10 p.m.-4 p.m.
- T 6:30 p.m.-8 p.m.
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Instructor:
Gregory Witkowski
Info - 3 points
ADVANCED DATA ANALYSIS
Prerequisites: W4315 and either another statistics course numbered above the 4200 or permission of instructor. Required for the major in statistics. Data analysis using a computer statistical package and selected exploratory data analysis subroutines. Topics include editing of data for errors, exploratory and standard techniques for one-way analysis of variance, linear regression, and two-way analysis of variance. Material is presented in case-study format.
- Department: Statistics
- F 6:10 p.m.-8:40 p.m.
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Instructor:
Demissie Alemayehu
h-index: 14 Info - 3 points
TOPICS IN MODERN STATISTICS
INTRO TO PROB GRAPHICAL MODELS
Topics in Modern Statistics will provide MA Statistics students with an opportunity to study a specialized area of statistics in more depth and to meet the educational needs of a rapidly growing field.
- Department: Statistics
- M 7 p.m.-9:30 p.m.
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Instructor:
Ori Shental
Info - 3 points
TOPICS IN MODERN STATISTICS
APP MACHINE LRNING IMAGE ANALY
Topics in Modern Statistics will provide MA Statistics students with an opportunity to study a specialized area of statistics in more depth and to meet the educational needs of a rapidly growing field.
- Department: Statistics
- W 7 p.m.-9:30 p.m.
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Instructor:
Xiaofu He
h-index: 21 Info - 3 points
TOPICS IN MODERN STATISTICS
COMMUNICATING DATA & STAT
Topics in Modern Statistics will provide MA Statistics students with an opportunity to study a specialized area of statistics in more depth and to meet the educational needs of a rapidly growing field.
- Department: Statistics
- TR 8:40 a.m.-9:55 a.m.
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Instructor:
Mark Hansen
Wikipedia Info - 3 points
RESEARCH DESIGN
- Department: Applied Analytics
- T 6:10 p.m.-8 p.m.
- M 6:10 p.m.-8 p.m.
- W 6:10 p.m.-8 p.m.
- F 10:10 a.m.-noon
- F 2:10 p.m.-4 p.m.
- M 8:10 p.m.-10 p.m.
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Instructor:
Laura A Sywulak
Info - 3 points