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.
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.
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.
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.
This course analyzes the ways in which philanthropists and nonprofit organizations plan for and respond to disasters. Disasters create immense need quickly. People have responded generously to many natural and human-created disasters that have led to thousands of victims either domestically or globally. The nonprofit sector has often played a leading role, functioning both on the front-lines with first responders and creating a second response that bridges the period of relief and rebuilding. New technologies have often been deployed to improve fundraising as well as disaster relief. Disasters create both a sense of community born of the common experience of suffering and exacerbate differences within communities as those of lowest means struggle the most to recover. Disaster relief and recovery is ripe with questions about who to help and how to best help, presenting ethical dilemmas for the best intentioned of nonprofit leaders. The course will focus on the United States but both readings and assignments include some international comparisons.
Narrative medicine, its practice and scholarship, is necessarily concerned with issues of trauma, body, memory, voice, and inter-subjectivity. However, to grapple with these issues, we must locate them in their social, cultural, political, and historical contexts. Narrative understanding helps unpack the complex power relations between North and South, state and worker, disabled body and able body, bread-earner and child-bearer, as well as self and the other (or, even,
selves
and
others
). If disease, violence, terror, war, poverty, and oppression manifest themselves narratively, then resistance, justice, healing, activism, and collectivity can equally be products of a narrative-based approach to ourselves and the world. This course explores the connections between narrative, health, and social justice. In doing so, it broadens the mandate of narrative medicine, challenging each of us to bring a critical, self-reflective eye to our scholarship, teaching, practice, and organizing. How are the stories we tell, and are told, manifestations of social injustice? How can we transform such stories into narratives of justice, health, and change?
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.
Prerequisites: STAT GR5205 Statistical inference without parametric model assumption. Hypothesis testing using ranks, permutations, and order statistics. Nonparametric analogs of analysis of variance. Non-parametric regression, smoothing and model selection.
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.
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.
Prerequisites: STAT GR5204 Introductory course on the design and analysis of sample surveys. How sample surveys are conducted, why the designs are used, how to analyze survey results, and how to derive from first principles the standard results and their generalizations. Examples from public health, social work, opinion polling, and other topics of interest.
Prerequisites: STAT GR5206 or the equivalent. The course will provide an introduction to Machine Learning and its core models and algorithms. The aim of the course is to provide students of statistics with detailed knowledge of how Machine Learning methods work and how statistical models can be brought to bear in computer systems - not only to analyze large data sets, but to let computers perform tasks that traditional methods of computer science are unable to address. Examples range from speech recognition and text analysis through bioinformatics and medical diagnosis. This course provides a first introduction to the statistical methods and mathematical concepts which make such technologies possible.
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.
Agriculture is highly dependent on stable climate conditions to produce the world’s food with sufficient nutritional quality at an affordable cost. Climate change is threatening the breadbaskets of the world with shifting rainfall, pests, and weather patterns. Farmers face enormous challenges in adapting to this volatility that is affecting their livelihoods and communities locally, and threatens the global food systems stability. Adaptation to these changes has become a high priority for policy makers, corporations, and investors around the world. Climate smart agriculture presents solutions to the existential threat to the global food supply by utilizing a range of tech enabled methods for producing more food with less resources. The challenge is daunting because there is no “one size fits all” solution. Instead, localized solutions that meet the social, environmental, and economic realities of farmers need to be developed, accelerated, and implemented.
This is a topics course in industrial organization intended for MA students. The focus of the class is to familiarize students with the way economists in academic, antitrust regulatory and private sector settings approach research questions related to topics such as conduct, pricing, competition or ownership and control in various market structures (e.g., homogenous product, differentiated product, two-sided, vertical markets). The goal of the course is threefold. For each of the market structures considered:
(i)
familiarize you with the foundational economic theories;
(ii)
provide you with the empirical tools you can apply in the future to conduct your own research; and
(iii)
introduce to you key antitrust issues regulators have been focusing on and approaches used in practice to analyze these issues by antitrust economists.
Provides a global review of ERM requirements of regulators, rating agencies, and shareholders. Addresses three industry sectors: (1) insurance; (2) banking; and (3) corporate.
The elective "Open Source Intelligence: Research for Conflict Analysis"
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.
Once known as the arsenal of Democracy, the birthplace of the automobile assembly line, and the model city of America, 21st Century Detroit was emblematic of deindustrialization, decay, and insolvency. Following the largest municipal bankruptcy in US history, Detroit is now being reframed in both local and national media as a comeback city with opportunity and possibility for all - urban pioneers, global investors, a creative class of new professionals, and suburbanites seeking a return to urban grit.
Despite these narratives, Detroit remains highly segregated - racially, geographically, economically, and socially. While downtown is prospering, neighborhoods are still largely blighted and contaminated with legacy uses that remain unremediated. Over 30,000 houses and other structures have been demolished in the past 8 years, a process that is under-regulated and contributes to both environmental and infrastructure harm. To the extent new investments are improving the condition of housing and infrastructure in some strategic areas, these investments are displacing long term residents who remain at risk of eviction or foreclosure from their homes. Detroit remains one of the poorest big city in America and the poverty that remains is seemingly intractable. At present, only 36% of residents earn a living wage.
Detroit’s present condition is rooted in a protracted history of racist laws, policies, and practices that deny full citizenship to Black Detroiters, undermine Democracy, and position the city as a poor colony within a thriving metropolis. Racism has disfigured the social, physical and economic landscape of Detroit to produce profound levels of neglect, abuse, and exploitation of its residents, resulting in wealth extraction, housing insecurity, healthy food and water scarcity, educational malpractice, and environmental destruction, all within the framework of wealth attraction, tax incentives, subsidized growth and capital accumulation in the greater downtown.
Through this course, we will examine the thesis that sustainability and racism cannot co-exist; that sustainability is rooted in inclusive social wellbeing now and in future generations, whereas racism is rooted in hoarding of power and resources for one dominant group. This hoarding of resources for a favored population impairs preservation for future generations. Furthermore, environmental racism disconnects the consequences of environmental destruction from its beneficiari
Once known as the arsenal of Democracy, the birthplace of the automobile assembly line, and the model city of America, 21st Century Detroit was emblematic of deindustrialization, decay, and insolvency. Following the largest municipal bankruptcy in US history, Detroit is now being reframed in both local and national media as a comeback city with opportunity and possibility for all - urban pioneers, global investors, a creative class of new professionals, and suburbanites seeking a return to urban grit.
Despite these narratives, Detroit remains highly segregated - racially, geographically, economically, and socially. While downtown is prospering, neighborhoods are still largely blighted and contaminated with legacy uses that remain unremediated. Over 30,000 houses and other structures have been demolished in the past 8 years, a process that is under-regulated and contributes to both environmental and infrastructure harm. To the extent new investments are improving the condition of housing and infrastructure in some strategic areas, these investments are displacing long term residents who remain at risk of eviction or foreclosure from their homes. Detroit remains one of the poorest big city in America and the poverty that remains is seemingly intractable. At present, only 36% of residents earn a living wage.
Detroit’s present condition is rooted in a protracted history of racist laws, policies, and practices that deny full citizenship to Black Detroiters, undermine Democracy, and position the city as a poor colony within a thriving metropolis. Racism has disfigured the social, physical and economic landscape of Detroit to produce profound levels of neglect, abuse, and exploitation of its residents, resulting in wealth extraction, housing insecurity, healthy food and water scarcity, educational malpractice, and environmental destruction, all within the framework of wealth attraction, tax incentives, subsidized growth and capital accumulation in the greater downtown.
Through this course, we will examine the thesis that sustainability and racism cannot co-exist; that sustainability is rooted in inclusive social wellbeing now and in future generations, whereas racism is rooted in hoarding of power and resources for one dominant group. This hoarding of resources for a favored population impairs preservation for future generations. Furthermore, environmental racism disconnects the consequences of environmental destruction from its beneficiari
Course Overview
Investors in residential and commercial real estate, those in infrastructure and supply-chain, to name a few examples, are exposed to risks of flooding, droughts and forest fires as a consequence of the reverberations of climate change on environmental factors and weather. Such risks are higher for stakeholders with properties close to the coast or in regions where drought and forest fires are increasing (e.g., the Western U.S.) as well as for financial institutions that finance their purchases and hold their securities. Risks associated with sea level rise, flooding, inundation and other extreme events have generally not been properly assessed nor quantified and it is currently hard for investors to assess the risks that they now face, and will face in the future, from climate change. Moreover, the consequences of climate change go beyond the financial and economic ones, as in the case of climate justice, in which the social cost of the climate change impacts is paid by those who are the least responsible and that are the most vulnerable from a socio-economic perspective.
The course will focus on fundamentals on economic and financial impacts of climate change. We will discuss the major impacts of climate change from a financial and climate perspective. This work will be spread throughout the semester through presentations by the teacher, guest speakers and in-class discussions from the readings. The class will also focus on specific topics for the required final project. Students will be able to use the SEPHER dataset, developed at Lamont and focusing on real estate, socio-vulnerability of people exposed to climate change impacts, with emphasis on racial issues, economic wealth and phenomena such as climate gentrification and housing. The students will be exposed to the dataset at the beginning of the course and will be taught how to visualize the data without any computer science knowledge.
Students will explore the state of the art of current literature on the topics described above and discuss in class about the most updated findings and their economic drivers or implications. Then, students will be exposed to the use of Geographic Information System (GIS) to map quantities of interest using SEPHER 2.0. With this powerful and yet simple tool, students will be able to visualize variables to analyze maps to develop ideas and support hypothesis integration and growth. The students will be exposed to training when they will be doing practical hands-on exercises to create
Course Overview
Investors in residential and commercial real estate, those in infrastructure and supply-chain, to name a few examples, are exposed to risks of flooding, droughts and forest fires as a consequence of the reverberations of climate change on environmental factors and weather. Such risks are higher for stakeholders with properties close to the coast or in regions where drought and forest fires are increasing (e.g., the Western U.S.) as well as for financial institutions that finance their purchases and hold their securities. Risks associated with sea level rise, flooding, inundation and other extreme events have generally not been properly assessed nor quantified and it is currently hard for investors to assess the risks that they now face, and will face in the future, from climate change. Moreover, the consequences of climate change go beyond the financial and economic ones, as in the case of climate justice, in which the social cost of the climate change impacts is paid by those who are the least responsible and that are the most vulnerable from a socio-economic perspective.
The course will focus on fundamentals on economic and financial impacts of climate change. We will discuss the major impacts of climate change from a financial and climate perspective. This work will be spread throughout the semester through presentations by the teacher, guest speakers and in-class discussions from the readings. The class will also focus on specific topics for the required final project. Students will be able to use the SEPHER dataset, developed at Lamont and focusing on real estate, socio-vulnerability of people exposed to climate change impacts, with emphasis on racial issues, economic wealth and phenomena such as climate gentrification and housing. The students will be exposed to the dataset at the beginning of the course and will be taught how to visualize the data without any computer science knowledge.
Students will explore the state of the art of current literature on the topics described above and discuss in class about the most updated findings and their economic drivers or implications. Then, students will be exposed to the use of Geographic Information System (GIS) to map quantities of interest using SEPHER 2.0. With this powerful and yet simple tool, students will be able to visualize variables to analyze maps to develop ideas and support hypothesis integration and growth. The students will be exposed to training when they will be doing practical hands-on exercises to create
Whether through a speech to key donors, a published op-ed column, an annual report or media interview, leaders of nonprofit organizations must be compelling storytellers. Although other courses in the Nonprofit Management M.S. program helpfully concentrate on the strategy and tactics of communications outreach and social media engagement, the intensive focus of this elective will be on developing students’ capacity for literate writing and speaking across a range of public forums and institutional challenges that face nonprofit organizations. Through a combination of readings, discussion and, most importantly, a diverse range of writing assignments and creative exercises, students will emerge with a new level of editorial proficiency in creating the kind of written and spoken communications that support a nonprofit’s development, promote its public service mission, and manage difficult political, legal and institutional issues that distract organizations from achieving their mission-driven goals. Students will learn best practices for crafting persuasive communications in an increasingly complex and time-sensitive media environment.
This course covers programming with applications to finance. The applications may include such topics as yield curve building and calibration, short rate models, Libor market models, Monte Carlo simulation, valuation of financial instruments such as options, swaptions and variance swaps, and risk measurement and management, among others. Students will learn about the underlying theory, learn coding techniques, and get hands-on experience in implementing financial models and systems.
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.
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.
Prerequisites: STAT GR5264 Available to SSP, SMP. Mathematical theory and probabilistic tools for modeling and analyzing security markets are developed. Pricing options in complete and incomplete markets, equivalent martingale measures, utility maximization, term structure of interest rates.
To make informed decisions about communication, we need a clear understanding of our audience and its motivations. We begin by asking the right questions and interpreting the results. This course covers essential market research methods, including quantitative and qualitative techniques. Students gain direct experience in collecting and analyzing data, developing insights and choosing research-driven communication strategies that meet client objectives.
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.
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.
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.
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.
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.
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.
Workshop-like course that addresses a variety of communication skills, including listening skills, presentation skills, leadership communications, conflict resolution, management interactions, and professional communication techniques.
Nonprofit organizations compete for scarce philanthropic and government funding and are expected to account for how these resources are utilized for the greater good. However, understanding how well nonprofit programs and services produce their desired outcomes can be a challenge. This course is designed to provide a broad – yet rigorous – overview of the knowledge and tools available to evaluate the effects of nonprofit and social impact programs and policies.