Understanding and interpreting large, quantitative data sets is increasingly central in political and social science. Whether one seeks to understand political communication, international trade, inter-group conflict, or other issues, the availability of large quantities of digital data has revolutionized the study of politics. Nonetheless, most data-related courses focus on statistical estimation, rather than on the related but distinctive problems of data acquisition, management and visualization--in a term, data science. This course addresses that imbalance by focusing squarely on data science. Leaving this course, students will be able to acquire, format, analyze, and visualize various types of political data using the statistical programming language R. This course is not a statistics class, but it will increase the capacity of students to thrive in future statistics classes. While no background in statistics or political science is required, students are expected to be generally familiar with contemporary computing environments (e.g. know how to use a computer) and have a willingness to learn a variety of data science tools. You are encouraged (but certainly not required) to register for both this course and PSCI 338 at the same time, as the courses cover distinct, but complimentary material.

Understanding and interpreting large, quantitative data sets is increasingly central in political and social science. Whether one seeks to understand political communication, international trade, inter-group conflict, or other issues, the availability of large quantities of digital data has revolutionized the study of politics. Nonetheless, most data-related courses focus on statistical estimation, rather than on the related but distinctive problems of data acquisition, management and visualization--in a term, data science. This course addresses that imbalance by focusing squarely on data science. Leaving this course, students will be able to acquire, format, analyze, and visualize various types of political data using the statistical programming language R. This course is not a statistics class, but it will increase the capacity of students to thrive in future statistics classes. While no background in statistics or political science is required, students are expected to be generally familiar with contemporary computing environments (e.g. know how to use a computer) and have a willingness to learn a variety of data science tools. You are encouraged (but certainly not required) to register for both this course and PSCI 338 at the same time, as the courses cover distinct, but complimentary material.

Understanding and interpreting large, quantitative data sets is increasingly central in political and social science. Whether one seeks to understand political communication, international trade, inter-group conflict, or other issues, the availability of large quantities of digital data has revolutionized the study of politics. Nonetheless, most data-related courses focus on statistical estimation, rather than on the related but distinctive problems of data acquisition, management and visualization--in a term, data science. This course addresses that imbalance by focusing squarely on data science. Leaving this course, students will be able to acquire, format, analyze, and visualize various types of political data using the statistical programming language R. This course is not a statistics class, but it will increase the capacity of students to thrive in future statistics classes. While no background in statistics or political science is required, students are expected to be generally familiar with contemporary computing environments (e.g. know how to use a computer) and have a willingness to learn a variety of data science tools. You are encouraged (but certainly not required) to register for both this course and PSCI 338 at the same time, as the courses cover distinct, but complimentary material.

Understanding and interpreting large, quantitative data sets is increasingly central in political and social science. Whether one seeks to understand political communication, international trade, inter-group conflict, or other issues, the availability of large quantities of digital data has revolutionized the study of politics. Nonetheless, most data-related courses focus on statistical estimation, rather than on the related but distinctive problems of data acquisition, management and visualization--in a term, data science. This course addresses that imbalance by focusing squarely on data science. Leaving this course, students will be able to acquire, format, analyze, and visualize various types of political data using the statistical programming language R. This course is not a statistics class, but it will increase the capacity of students to thrive in future statistics classes. While no background in statistics or political science is required, students are expected to be generally familiar with contemporary computing environments (e.g. know how to use a computer) and have a willingness to learn a variety of data science tools. You are encouraged (but certainly not required) to register for both this course and PSCI 338 at the same time, as the courses cover distinct, but complimentary material.

Understanding and interpreting large, quantitative data sets is increasingly central in political and social science. Whether one seeks to understand political communication, international trade, inter-group conflict, or other issues, the availability of large quantities of digital data has revolutionized the study of politics. Nonetheless, most data-related courses focus on statistical estimation, rather than on the related but distinctive problems of data acquisition, management and visualization--in a term, data science. This course addresses that imbalance by focusing squarely on data science. Leaving this course, students will be able to acquire, format, analyze, and visualize various types of political data using the statistical programming language R. This course is not a statistics class, but it will increase the capacity of students to thrive in future statistics classes. While no background in statistics or political science is required, students are expected to be generally familiar with contemporary computing environments (e.g. know how to use a computer) and have a willingness to learn a variety of data science tools. You are encouraged (but certainly not required) to register for both this course and PSCI 338 at the same time, as the courses cover distinct, but complimentary material.

Understanding and interpreting large, quantitative data sets is increasingly central in political and social science. Whether one seeks to understand political communication, international trade, inter-group conflict, or other issues, the availability of large quantities of digital data has revolutionized the study of politics. Nonetheless, most data-related courses focus on statistical estimation, rather than on the related but distinctive problems of data acquisition, management and visualization--in a term, data science. This course addresses that imbalance by focusing squarely on data science. Leaving this course, students will be able to acquire, format, analyze, and visualize various types of political data using the statistical programming language R. This course is not a statistics class, but it will increase the capacity of students to thrive in future statistics classes. While no background in statistics or political science is required, students are expected to be generally familiar with contemporary computing environments (e.g. know how to use a computer) and have a willingness to learn a variety of data science tools. You are encouraged (but certainly not required) to register for both this course and PSCI 338 at the same time, as the courses cover distinct, but complimentary material.

Understanding and interpreting large, quantitative data sets is increasingly central in political and social science. Whether one seeks to understand political communication, international trade, inter-group conflict, or other issues, the availability of large quantities of digital data has revolutionized the study of politics. Nonetheless, most data-related courses focus on statistical estimation, rather than on the related but distinctive problems of data acquisition, management and visualization--in a term, data science. This course addresses that imbalance by focusing squarely on data science. Leaving this course, students will be able to acquire, format, analyze, and visualize various types of political data using the statistical programming language R. This course is not a statistics class, but it will increase the capacity of students to thrive in future statistics classes. While no background in statistics or political science is required, students are expected to be generally familiar with contemporary computing environments (e.g. know how to use a computer) and have a willingness to learn a variety of data science tools. You are encouraged (but certainly not required) to register for both this course and PSCI 338 at the same time, as the courses cover distinct, but complimentary material.

Freshmen seminars are small, substantive courses taught by members of the faculty and open only to freshmen. These seminars offer an excellent opportunity to explore areas not represented in high school curricula and to establish relationships with faculty members around areas of mutual interest. See www.college.upenn.edu/admissions/freshmen.php

This course will provide an overview of major figures and themes of modern political thought. We will focus on themes and questions pertinent to political theory in the modern era, particularly focusing on the relationship of the individual to community, society, and state. Although the emergence of the individual as a central moral, political, and conceptual category arguably began in earlier eras, it is in the seventeenth century that it takes firm hold in defining the state, political institutions, moral thinking, and social relations. The centrality of "the individual" has created difficulties, even paradoxes, for community and social relations, and political theorists have struggled to reconicle those throughout the modern era. We will consider the political forms that emerged out of those struggles, as well as the changed and distinctly "modern" conceptualizations of political theory such as freedom, responsibilty, justice, rights and obligations, as central categories for organizing moral and political life.

This course examines the dynamics of political and economic change in twentieth century Latin America, with the goal of achieving an understanding of contemporary politics in the region. We will analyze topics such as the incorporation of the region to the international economy and the consolidation of oligarchic states (1880s to 1930s), corporatism, populism, and elict pacts (1930s and 1940s), social revolution, democratic breakdown, and military rule (1960s and 1970s), transitions to democracy and human rights advocacy (1980s), makret-oriented reforms (1990s), and the turn to the left of current governments (2000s). The course will draw primarily from the experiences of Argentina, Brazil, Colombia, Chile and Mexico. No prior knowledge of the region is required.