2015-2016 2016-2017 2017-2018 2018-2019 2019-2020
Browse
by subject...
    Schedule
view...
 

151 - 160 of 171 results for: all courses

POLISCI 150C: Causal Inference for Social Science (POLISCI 355C)

Causal inference methods have revolutionized the way we use data, statistics, and research design to move from correlation to causation and rigorously learn about the impact of some potential cause (e.g., a new policy or intervention) on some outcome (e.g., election results, levels of violence, poverty). This course provides an introduction that teaches students the toolkit of modern causal inference methods as they are now widely used across academic fields, government, industry, and non-profits. Topics include experiments, matching, regression, sensitivity analysis, difference-in-differences, panel methods, instrumental variable estimation, and regression discontinuity designs. We will illustrate and apply the methods with examples drawn from various fields including policy evaluation, political science, public health, economics, business, and sociology. Prerequisite: POLISCI 150A.
Terms: Spr | Units: 5 | UG Reqs: WAY-AQR

POLISCI 241S: Spatial Approaches to Social Science (ANTHRO 130D, ANTHRO 230D, URBANST 124)

This multidisciplinary course combines different approaches to how GIS and spatial tools can be applied in social science research. We take a collaborative, project oriented approach to bring together technical expertise and substantive applications from several social science disciplines. The course aims to integrate tools, methods, and current debates in social science research and will enable students to engage in critical spatial research and a multidisciplinary dialogue around geographic space.
Terms: Win | Units: 5 | UG Reqs: WAY-AQR, WAY-SI

POLISCI 247A: Games Developing Nations Play (ECON 162, POLISCI 347A)

If, as economists argue, development can make everyone in a society better off, why do leaders fail to pursue policies that promote development? The course uses game theoretic approaches from both economics and political science to address this question. Incentive problems are at the heart of explanations for development failure. Specifically, the course focuses on a series of questions central to the development problem: Why do developing countries have weak and often counterproductive political institutions? Why is violence (civil wars, ethnic conflict, military coups) so prevalent in the developing world, and how does it interact with development? Why do developing economies fail to generate high levels of income and wealth? We study how various kinds of development traps arise, preventing development for most countries. We also explain how some countries have overcome such traps. This approach emphasizes the importance of simultaneous economic and political development as two different facets of the same developmental process. No background in game theory is required.
Terms: Win | Units: 3-5 | UG Reqs: WAY-AQR, WAY-SI

POLISCI 251A: Introduction to Machine Learning for Social Scientists

This course introduces techniques to collect, analyze, and utilize large collections of data for social science inferences. The ultimate goal of the course is to familiarize students to modern machine learning techniques and provide the skills necessary to apply these methods widely. Students will leave the course equipped with a broad understanding of machine learning and on how to continue building new skills. This is an introductory course, so most the lectures and problem sets will be focused on the intuition and the mechanics behind machine learning concepts rather than the mathematical fundamentals. There are no formal prerequisites for the course, but calculus and introductory statistics are strongly recommended. Students are not expected to have any programming knowledge, and the course will be centered around bite-size assignments that will help build R coding and statistical skills from scratch.
Last offered: Summer 2018 | UG Reqs: WAY-AQR

PSYCH 10: Introduction to Statistical Methods: Precalculus (STATS 60, STATS 160)

Techniques for organizing data, computing, and interpreting measures of central tendency, variability, and association. Estimation, confidence intervals, tests of hypotheses, t-tests, correlation, and regression. Possible topics: analysis of variance and chi-square tests, computer statistical packages.
Terms: Aut, Win, Spr, Sum | Units: 5 | UG Reqs: GER:DB-Math, WAY-AQR, WAY-FR

PUBLPOL 104: Economic Policy Analysis (ECON 150, PUBLPOL 204)

The relationship between microeconomic analysis and public policy making. How economic policy analysis is done and why political leaders regard it as useful but not definitive in making policy decisions. Economic rationales for policy interventions, methods of policy evaluation and the role of benefit-cost analysis, economic models of politics and their application to policy making, and the relationship of income distribution to policy choice. Theoretical foundations of policy making and analysis, and applications to program adoption and implementation. Prerequisites: ECON 50 and ECON 102B. Undergraduate Public Policy students are required to take this class for a letter grade and enroll in this class for five units.
Terms: Win | Units: 4-5 | UG Reqs: WAY-AQR

PUBLPOL 105: Empirical Methods in Public Policy (PUBLPOL 205)

Methods of empirical analysis and applications in public policy. Emphasis on causal inference and program evaluation. Public policy applications include health, education, and labor. Assignments include hands-on data analysis, evaluation of existing literature, and a final research project. Objective is to obtain tools to 1) critically evaluate evidence used to make policy decisions and 2) perform empirical analysis to answer questions in public policy. Prerequisite: ECON 102B. Enrollment is limited to Public Policy students. Public Policy students must take the course for a letter grade.
Terms: Win, Spr | Units: 4-5 | UG Reqs: WAY-AQR, WAY-SI

PUBLPOL 118X: Shaping the Future of the Bay Area (CEE 118X, CEE 218X, ESS 118X, ESS 218X, GEOLSCI 118X, GEOLSCI 218X, GEOPHYS 118X, GEOPHYS 218X, POLISCI 224X)

The complex urban problems affecting quality of life in the Bay Area, from housing affordability and transportation congestion to economic vitality and social justice, are already perceived by many to be intractable, and will likely be exacerbated by climate change and other emerging environmental and technological forces. Changing urban systems to improve the equity, resilience and sustainability of communities will require new collaborative methods of assessment, goal setting, and problem solving across governments, markets, and communities. It will also require academic institutions to develop new models of co-production of knowledge across research, education, and practice. This XYZ course series is designed to immerse students in co-production for social change. The course sequence covers scientific research and ethical reasoning, skillsets in data-driven and qualitative analysis, and practical experience working with local partners on urban challenges that can empower students to more »
The complex urban problems affecting quality of life in the Bay Area, from housing affordability and transportation congestion to economic vitality and social justice, are already perceived by many to be intractable, and will likely be exacerbated by climate change and other emerging environmental and technological forces. Changing urban systems to improve the equity, resilience and sustainability of communities will require new collaborative methods of assessment, goal setting, and problem solving across governments, markets, and communities. It will also require academic institutions to develop new models of co-production of knowledge across research, education, and practice. This XYZ course series is designed to immerse students in co-production for social change. The course sequence covers scientific research and ethical reasoning, skillsets in data-driven and qualitative analysis, and practical experience working with local partners on urban challenges that can empower students to drive responsible systems change in their future careers. The Autumn (X) course is specifically focused on concepts and skills, and completion is a prerequisite for participation in the Winter (Y) and/or Spring (Z) practicum quarters, which engage teams in real-world projects with Bay Area local governments or community groups. X is composed of four modules: (A) participation in two weekly classes which prominently feature experts in research and practice related to urban systems; (B) reading and writing assignments designed to deepen thinking on class topics; (C) fundamental data analysis skills, particularly focused on Excel and ArcGIS, taught in lab sessions through basic exercises; (D) advanced data analysis skills, particularly focused on geocomputation in R, taught through longer and more intensive assignments. X can be taken for 3 units (ABC), 4 units (ACD), or 5 units (ABCD). Open to undergraduate and graduate students in any major. For more information, visit http://bay.stanford.edu.
Terms: Aut | Units: 3-5 | UG Reqs: WAY-AQR, WAY-SI

SINY 150: Biology, Technology, and Society: The City as a Human Life Support System

While environmental issues related to cities are often considered in the context of climate change, this course will use New York City as a lab to explore how dense global cities deal with their intense biological needs clean drinking water, sanitation and sewage, public health, food supply the ongoing management and maintenance of which occupy a surprising portion of the infrastructure, management, and tax expenditure of most city governments.
Last offered: Spring 2018 | UG Reqs: WAY-AQR

SINY 162: Sustainable and Resilient Urban Systems in NYC

The objective of the course is to develop a qualitative and quantitative understanding of sustainability and resilience for major urban areas. The first part of the quarter will focus on sustainability and the second on resilience. n nThe course will commence with an overview of the 17 Sustainable Development Goals (SDG) as defined by the United Nations and how New York City is working towards these goals. The components and pillars that lead to a sustainable urban environment will be defined and corresponding metrics will be used to quantify sustainability utilizing simple data analytics tools. Challenges to meeting these goals will be an important part of reading and project assignments. Examples of sustainability efforts within New York City (NYC) include the development of new parks or renewal of industrial areas for recreational use, design of green buildings, rooftop farms and gardens, and the renovation of transportation facilities as focal points. Field trips will include visit more »
The objective of the course is to develop a qualitative and quantitative understanding of sustainability and resilience for major urban areas. The first part of the quarter will focus on sustainability and the second on resilience. n nThe course will commence with an overview of the 17 Sustainable Development Goals (SDG) as defined by the United Nations and how New York City is working towards these goals. The components and pillars that lead to a sustainable urban environment will be defined and corresponding metrics will be used to quantify sustainability utilizing simple data analytics tools. Challenges to meeting these goals will be an important part of reading and project assignments. Examples of sustainability efforts within New York City (NYC) include the development of new parks or renewal of industrial areas for recreational use, design of green buildings, rooftop farms and gardens, and the renovation of transportation facilities as focal points. Field trips will include visits to the Highline, the Hudson Yard and the Bank of America building. n nResilience of urban systems will be the focus of the second half of the class. Issues of resilience will be discussed in relation to major disasters including floods, extreme storms and climate change. The 7 global resilience targets will be identified according to the Sendai Framework for Disaster Risk Reduction. The major components of resilience will be reviewed in class followed by a visit to or by a representative from the 100 Resilient City Initiative supported by the Rockefeller Foundation. The Superstorm Sandy in 2012 will be used as a case study to identify the disaster impact to the urban environment in NYC. We will discuss the emergency response of the City after Sandy and assess the performance of the NYC resilience plan. We will explore how New York City is preparing to respond and recover from future major disasters as part of the 100 Resilient Cities Initiative supported by the Rockefeller Foundation. n nNovel technologies will be discussed in terms of their implications for disaster resilience and sustainability. We will delve into a case study showing how modern and decentralized power systems with rooftop solar panels and microgrids can make NYC more resilient and sustainable.
Terms: Aut, Win, Spr | Units: 3-4 | UG Reqs: WAY-AQR
Filter Results:
term offered
updating results...
number of units
updating results...
time offered
updating results...
days
updating results...
UG Requirements (GERs)
updating results...
component
updating results...
career
updating results...
© Stanford University | Terms of Use | Copyright Complaints