SA.100 (Core Courses)

This course is a survey of postwar American Foreign Policy, intended to give students a basic literacy in the field, including a grasp of the pre-war foundations of US diplomacy. The class sessions will attempt to deal with all of the topics contained in the syllabus, but some areas will inevitably be treated in more depth than others. Students are urged to read as widely as possible and to bring questions of interest to the attention of the instructor.

Prerequisite(s): Students may not register for this class if they have already received credit for SA.100.720[C]

This is a survey course in comparative politics that provides an overview of major theoretical approaches and issue areas in the field of comparative politics. It exposes students to a wide range of themes through reading of foundational work each week. The course starts by introducing competing theoretical approaches adopted by scholars of the field, including the state-centric, comparative historical, rational choice, and institutional perspectives. Using these approaches, the course then proceeds to examine issue areas such as political economy of developed and developing countries, democracy and authoritarianism, voting and parties, nationalism and ethnic politics, and the international context of domestic politics.

Prerequisite(s): Students may not register for this class if they have already received credit for SA.100.750[C]

Provides an historical and global geopolitical framework for understanding how the modern global system has evolved. Focuses on three broad motifs: (1) the dialectical character of the European state system, (2) the relationship of Europe to the rest of the world and (3) the progressive rise of non-European powers and the growing challenge these have posed to Europe’s dominant position in the world. Concludes with reflections on the contemporary international system and its principal actors, with an eye to defining its prospects in the 21st century.

Prerequisite(s): Students may not register for this class if they have already received credit for SA.100.771[C]

This course surveys a variety of broad theoretical approaches to analyzing international politics. Examines approaches to the study of power, state interests, peace and war, international law, and economic cooperation; presents a critique of realist, liberal, and constructivist conceptions of international politics; and introduces basic methodology, weighing the evidence to assess the relative merits of theories.

Prerequisite(s): Students may not register for this class if they have already received credit for SA.100.761[C]

In this course, we will consider international relations through the prisms of order and disorder. Drawing on a variety of social scientific traditions, we will explore distinct theoretical perspectives (orthodox and critical) to map out the contours of war-making, state-building, and diplomacy from the historical to the present. We will attend to the evolution of key concepts, trends, and debates that have framed the study and practice of foreign affairs. In so doing, we will contend with the interplay between politics and law, state and non-state, interest and ideology, competition and cooperation. Ultimately, we aim to analyze contemporary global challenges with an eye to imagining future possibilities for governance, conflict management, peace, and justice.

Prerequisite(s): Students may not register for this class if they have already received credit for SA.100.201[C] OR SA.100.202[C]

Provides comprehensive introduction to econometrics. Develops tools for estimating functional relationships and critically reading empirical studies that use different econometric techniques; presents assumptions of multivariate regression and discusses the most common econometric problems and the potential consequences and remedies; and discusses omitted variables, sample selection, heteroscedasticity, autocorrelation, multicollinearity and use of discrete variables. Introduces instrumental variable technique. Uses statistical software in applied exercises.

Prerequisite(s): Statistics for Data Analysis (SA.340.710) is a pre-requisite for this course (SA.100.401);Students may not register for Econometrics if they have already received credit for SA.340.710[C];;SA.100.501[C] OR SA.340.709[C] OR SA.999.702[C]

Focuses on recent empirical issues in international economics and development. Examines both econometric methods and findings. Emphasizes the econometrics models used, estimation problems encountered and techniques developed to address these problems. Aims to evaluate evidence from existing research and extend understanding of econometric methods to carry out independent research. Prerequisite: Econometrics.

Prerequisite(s): Students may not register for this class if they have already received credit for SA.340.731[C];SA.100.401[C] OR SA.340.710[C]

Macroeconometrics develops the basic tools of time series to design dynamic models that explain the data, discriminate among alternative theories, and are used to forecast. The focus is on the following questions: Why is time a big deal for Macroeconometrics? How can one model the dynamics of the response of one variable to changes in its determinants? Can I treat the parameters as constant? What is forecast accuracy? Should the focus be on a single equation or on a system of equations? What are the assumptions, weaknesses, and strengths? Are there alternative methods of addressing a given issue? The course develops and applies this modeling strategy to understand the interactions between the price of oil and the value of the dollar. I will provide the data for these applications. Students write three “papers” that constitute the three sections of an integrated paper. The first three papers focus on (1) data properties; (2) assessing the inferential quality of the estimating equations; and (3) assessing forecast accuracy relative to alternative models. The fourth paper integrates the three papers into a reliable econometric model to explain and forecast the price of oil and the value of the U.S. dollar.

Prerequisite(s): SA.100.401[C] OR SA.340.710[C];Students may not register for this class if they have already received credit for SA.340.735[C]

This course covers the most common quantitative and qualitative research methods used in practical applications such as by program implementers and their partners and in policy analysis. It focuses mainly on observational methods and those for primary data collection, but will touch on longitudinal research designs, experiments, and secondary data analysis to situate observational research in context and consider creative combinations of designs and methods to answer complex questions. Students will develop the ability to design and implement surveys, focus groups, and interviews, including ethical approval, sampling procedures, and developing budgets and timelines. Additional quantitative and qualitative data collection and analysis methods are reviewed as well. Ethical issues are considered extensively throughout the course.

Prerequisite(s): Students may not register for this class if they have already received credit for SA.400.700[C];Cannot take if you have already received credit for SA.100.416[C]

This course introduces students to research methods that are commonly employed today in the field of international relations. The focus of the course is on research designs aimed at establishing causal inferences. There are four main sections to the class, each of which covers one major type of research design. The first section focuses on qualitative research methods. The second section turns to quantitative methods, particularly methods used for analyzing observational data (i.e. non-experimental data). In section III, we study experimental methods. The final section provides an overview of various quasi-experimental methods.

Prerequisite(s): SA.100.401[C] OR SA.340.710[C];Students may not register for this class if they have already received credit for SA.600.767[C]

The purpose of this course is to help students work through the challenge of understanding risk in international political and economic relations. That challenge is both methodological and substantive. Students will have to tackle ‘how’ we understand and ‘what’ we understand at the same time. Along the way, they will have to consider those things we cannot understand or anticipate with any meaningful degree of precision. They will have to deal with the ‘uncertainty’ that lies beyond the boundaries of ‘risk’. The subject matter is open-ended. Virtually every aspect of politics or economics can be cast in terms of risk and uncertainty, no matter whether we look to the future or reflect upon the past. Therefore, the course builds on a thematically structured, case study approach. Each week introduces a new principle that is useful in understanding risk; each week provides cases that illustrate the usefulness of that new principle. Moreover, as our understanding of risk becomes more sophisticated, the cases become more complex. Theultimate goal is to be able to analyze matters of risk and uncertainty as they manifest around decisions taken by leaders in government or business in the real world.

Research in the social sciences calls upon different methods for gathering information, interpreting data, drawing inferences, and advancing arguments. Qualitative methods rely on direct observation, narrative forms, and tools such as interviews, archival sources, media, participant observation, ethnographic analysis and historical documentation. Qualitative approaches may draw upon inductive techniques (assessing evidence directly) and deductive reasoning (drawing on stylized or logical relationships) when identifying patterns and crafting propositions. The purposes of qualitative methods are broadly similar to those of quantitative methods: drawing inferences (resilient generalizations) from evidence, developing causal arguments about the sources and mechanisms of events, and testing propositions about political behavior. Qualitative methods are also frequently partnered with quantitative methods in "mixed-method" research designs. However, the assumptions and procedures of qualitative methodology are distinct.Initial registration for this course is restricted to PhD students. Interested non-PhD students can register via SIS and request “Pending Approval”. Separately, students must submit a maximum one-page statement of interest and relevant experience to Professor Lewis at plewis18@jhu.edu; please copy jyoungs1@jhu.edu. Prof. Lewis will review and decide whether or not to approve.

Prerequisite(s): Students may not register for this class if they have already received credit for SA.600.774[C]

This class introduces students to different research designs in comparative and international analysis. The discussion will be based mainly on examples of high-impact studies. Methods covered include cross-national large-N survey, ethnography, interview, small-N comparison, paired comparison, and process tracing. Through intensive engagement with the readings, which are composed of classics and cutting-edge research, students are expected to develop critical appreciation of the diverse methodological strategies underlying different empirical studies and the capability of employing some of the methods in their research.

Today's world relies a lot on the accumulation, presentation, and interpretation of large quantities of information. Statistics and Econometrics are tools that enable us to organize our data in an efficient manner and provide us with methods that help to understand the relationships that occur in our data and our increasingly complex world. In this course, we will draw examples from multiple disciplines, such as political science and economics, to demonstrate how to search for and evaluate patterns in large amounts of data, as well as to interpret what these patterns tell us about the world. The course develops tools for estimating functional relationships and critically reading empirical studies that use different econometric techniques.

Prerequisite(s): SA.100.501[C] OR SA.340.709[C] OR SA.999.702[C] OR SA.630.724[C]

forthcoming...

The course is a critical review of human-centered quantitative and qualitative research applications in international affairs, with a particular focus on learning the tools used by social scientists to evaluate the quality and feasibility of different research approaches in developing country contexts. The first half of the course delves into the practical uses of validity theory as the gold standard to assess the victories and pitfalls of experiments, quasi-experiments and non-experiments in real-world cases around the world. The second half of the course is devoted to understanding qualitative research methods (in-depth interviews, focus groups, and a variety of observational tools such as photography and graphic novel techniques), and learning to identify the strengths and weaknesses of qualitative work in hard-to-access contexts across Africa, Asia and Latin America. The course provides a practical knowledge foundation for professionals who aspire to critically assess the real value of quantitative and qualitative evidence presented to them, while it helps them to determine the right opportunities to generate new knowledge for more informed and effective policy and program design.

Relationships between individuals and the social networks those relationships form can be crucial to explaining important sociopolitical outcomes, such as a group's power dynamics, the spread of information, or governmental decision-making processes. This course introduces students to the foundations of social network analysis, an increasingly popular approach for social scientists interested in understanding interdependence between actors and the properties of social network structures. Starting with an introduction to the conceptual foundations of social network analysis methods, the course then moves to consideration of their contemporary applications to understanding phenomena in international affairs as diverse as wartime mobilization or state status.

The course is a critical review of human-centered quantitative and qualitative research applications in international affairs, with a particular focus on learning the tools used by social scientists to evaluate the quality and feasibility of different research approaches in developing country contexts. The first half of the course delves into the practical uses of validity theory as the gold standard to assess the victories and pitfalls of experiments, quasi-experiments and non-experiments in real-world cases around the world. The second half of the course is devoted to understanding qualitative research methods (in-depth interviews, focus groups, and a variety of observational tools such as photography and graphic novel techniques), and learning to identify the strengths and weaknesses of qualitative work in hard-to-access contexts across Africa, Asia and Latin America. The course provides a practical knowledge foundation for professionals who aspire to critically assess the real value of quantitative and qualitative evidence presented to them, while it helps them to determine the right opportunities to generate new knowledge for more informed and effective policy and program design.

Prerequisite(s): Cannot take if you have already received credit for SA.100.406[C];Cannot take if you have already received credit for SA.100.414[C]

This course teaches students how to do field research. We will explore various field methods, including participant-observation, formal and informal interviews, network mapping, and ethnographic photography and video. In addition to weekly readings, students will immerse themselves in the actual doing of fieldwork by carrying out a mini field project during the semester in DC. Examples of field sites students can explore for their projects can include: courts, community organizations, religious institutions, activist networks, newsrooms, political institutions.

This course will focus on the history of modern international relations in order to train students in the use of historical, qualitative, and empirical methods. Students will work with primary sources and learn how to use these methods with those sources to build their own historical, qualitative arguments.

Nowadays datasets that have relevance for managerial decisions are accumulating at an incredible rate due to a host of technological advances. Electronic data capture has become inexpensive and ubiquitous as a by-product of innovations such as the internet, e-commerce, electronic banking, bar-code readers, and intelligent machines. Such datasets are often stored in data warehouses specifically intended for management decision support. Data mining is a rapidly growing field that is concerned with developing techniques to assist managers to make intelligent use of these repositories. Many successful applications have been reported in areas such as credit rating, fraud detection, database marketing, customer relationship management, stock market investments, and so on. The field of data mining has evolved from the disciplines of statistics and artificial intelligence. This course will examine methods and Machine Learning algorithms that have emerged from both fields and proven to be of value in recognizing patterns and making predictions. We will survey applications and provide an opportunity for hands-on experimentation with Machine Learning algorithms for data mining using Python. Prerequisite: Statistics for Data Analysis.

This course prepares students to conduct field research. Students will acquire methodological skills and data collection strategies that have broad application to research in international development. The course covers a range of field research methods, including ethnography, interviews, focus groups, surveys, and field experiments, as well as the logistical and ethical aspects of field research design.

Prerequisite(s): Students may not register for this class if they have already received credit for SA.100.406[C] OR SA.100.416[C]

This is an applied course on big data analytics with focus on data mining. R will be the main tool for problem solving with Python as the other option. Topics will cover data visualization, exploratory analysis, association rules, classification and regression trees, deep learning (neural networks), text mining, and social network analysis.Prerequisites:General understanding and experience with statistical models, including multivariable regression models, analysis of variance, and test of hypotheses. No previous programing experience is required, and the textbook offers extended code that can be used directly or modified.

Prerequisite(s): Students may not register for this class if they have already received credit for SA.510.131[C]

Covers basic statistical tools for data analysis. Emphasizes facility in problem-solving in statistical inference and two-variable regression and correlation analysis. Presents descriptive statistics, probability and probability distributions and their use in hypothesis testing. Uses computer to solve problems and to reinforce statistical concepts.

Prerequisite(s): Students may not register for this class if they have already received credit for SA.340.709[C]