|
CRIM 100-401 |
Criminology |
Viet Hoang Nguyen |
|
MW 01:45 PM-03:15 PM |
|
This introductory course examines the multi-disciplinary science of law-making, law-breaking, and law-enforcing. It reviews theories and data predicting where, when, by whom and against whom crimes happen. It also addresses the prevention of different offense types by different kinds of offenders against different kinds of people. Police, courts, prisons, and other institutions are critically examined as both preventing and causing crime. This course meets the general distribution requirement. |
|
SOCI233401 |
Society sector (all classes) |
<span class="penncourse-course-notes">Course is available to Freshmen and Upperclassmen.</span> |
|
|
|
|
|
CRIM 250-001 |
Statistics For the Social Sciences I |
Maria Cuellar |
|
MW 10:15 AM-11:45 AM |
|
Statistical techniques and quantitative reasoning are essential tools for properly examing questions in the social sciences. This course introduces students to the concepts of probability, estimation, confidence intervals, and how to use the statistical concepts and methods to answer social science questions. The course will require the use of R, a free, open source statistical analysis program. This course has been approved for the quantitative data analysis requirement (QDA). |
|
|
|
|
|
https://pennintouchdaemon.apps.upenn.edu/pennInTouchProdDaemon/jsp/fast.do?webService=syllabus&term=2021C&course=CRIM250001 |
|
|
|
CRIM 280-301 |
Neighbrhd Dyn. of Crime |
John M Macdonald |
|
MW 01:45 PM-03:15 PM |
|
Crime varies in time, space and populations as it reflects ecological structures and the routine social interactions that occur in daily life. Concentrations of crime can be found among locations, with antisocial activities like assaults and theft occurring at higher rates because of the demographic make-up of people (e.g. adolescents) or conflicts (e.g. competing gangs), for reasons examined by ecological criminology. Variation in socio-demographic structures (age, education ratios, and the concentration of poverty) and the physical environment (housing segregation, density of bars, street lighting) predicts variations between neighborhoods in the level of crime and disorder. Both ethnographic and quantitative research methods are used to explore the connections between the social and physical environment of areas and antisocial behavior. |
|
|
|
|
|
|
|
|
|
CRIM 315-001 |
Am Death Pen. Thry & Pra |
Thomas W Dolgenos |
|
CANCELED |
|
Over the past forty years, in response to controversy over the American death penalty, the Supreme Court has created a framework of rules designed to make the death penalty conform to current societal standards. In this course, we will identify the critical issues identified by the courts (and the critics) in light of the practical realities of capital litigation, and we will ask whether the efforts to address these issues have been successful. The class will use specific case examples to identify the critical points in a death penalty case- for example, the decision to designate a prosecution as "capital", the performance of defense counsel, the penalty decision, and the method of execution. These critical stages will provide a platform for discussing critical issues like the proper limits of discretion; bias; cruelty; and the decision to disqualify certain groups of people from capital punishment (the mentally disabled, minors). |
|
|
|
|
|
|
|
|
|
CRIM 402-401 |
Data Analytics in R |
Greg Ridgeway |
|
TR 01:45 PM-03:15 PM |
|
This course covers the tools and techniques to acquire, organize, link and visualize complex data in order to answer questions about crime and the criminal justice system. The course is organized around key questions about police shootings, victimization rates, identifying crime hotspots, calculating the cost of crime, and finding out what happens to crime when it rains. On the way to answer these questions, the course will cover topics including data sources, basic programming techniques, SQL, regular expressions, webscraping, and working with geographic data. The course will use R, an open-source, object oriented scripting language with a large set of available add-on packages. |
|
SOCI605401, CRIM602401 |
|
|
|
https://pennintouchdaemon.apps.upenn.edu/pennInTouchProdDaemon/jsp/fast.do?webService=syllabus&term=2021C&course=CRIM402401 |
|
|
|
CRIM 410-301 |
Research Seminar in Experiments in Crime and Justice |
Aurelie Ouss |
|
T 08:30 AM-11:30 AM |
|
This seminar focuses on examining data from experiments in criminology including: randomized controlled trials of criminal justice policies, "natural" experiments in crime, and other quasi-experimental studies. A series of experiments conducted by Penn scholars and elsewhere will be examined. This seminar also guides criminology majors in writing a research proposal for their thesis. Students will learn about how to formulate a research question, develop a review of the literature, and how to apply necessary empirical methods. The final paper for this course will be a research proposal that can serve as the basis for the student's senior thesis and to satisfy the senior capstone requirement. Readings will come from the disciplines of criminology, sociology, psychology, economics, and urban planning. Prerequisite: Any statistics or research methods course leading to familiarity with Excel, SPSS, R, Stata, SAS, Matlab, or NumPy. |
|
|
|
|
|
|
|
|
|
CRIM 536-401 |
Quantitative Methods I |
Hans-Peter Kohler |
|
TR 12:00 PM-01:00 PM |
|
This course is an introduction to the practice of statistics in social and behavioral sciences. It is open to beginning graduate students and--with the permission of the instructor--advanced undergraduates. Topics covered include the description of social science data, in graphical and non-graphical form; correlation and other forms of association, including cross-tabulation; bivariate regression; an introduction to probability theory; the logic of sampling; the logic of statistical inference and significance tests. There is a lecture twice weekly and a mandatory "lab." |
|
SOCI535401, DEMG535401 |
|
<span class="penncourse-course-notes">Registration also required for Recitation (see below)</span> |
|
https://pennintouchdaemon.apps.upenn.edu/pennInTouchProdDaemon/jsp/fast.do?webService=syllabus&term=2021C&course=CRIM536401 |
|
|
|
CRIM 600-301 |
Pro-Sem in Criminology |
John M Macdonald |
|
M 08:30 AM-11:30 AM |
|
This course provides an overview of the leading criminological theories of crime. The central focus is on the major theories of crime developed over the past century from the disciplines of economics, psychology, and sociology. The course will focus on the application of social science research as a way to evaluate theories of crime. Special attention is devoted to the issues of measurement of crime and what is known from the available empirical data. In addition, the course will focus on how these theoretical perspectives relate to public policy responses to crime. |
|
|
|
<span class="penncourse-course-notes">Undergraduates Need Permission</span> |
|
|
|
|
|
CRIM 602-401 |
Data Analytics in R |
Greg Ridgeway |
|
TR 01:45 PM-03:15 PM |
|
This course covers the tools and techniques to acquire, organize, link and visualize complex data in order to answer questions about crime and the criminal justice system. The course is organized around key questions about police shootings, victimization rates, identifying crime hotspots, calculating the cost of crime, and finding out what happens to crime when it rains. On the way to answer these questions, the course will cover topics including data sources, basic programming techniques, SQL, regular expressions, webscraping, and working with geographic data. The course will use R, an open-source, object oriented scripting language with a large set of available add-on packages. |
|
SOCI605401, CRIM402401 |
|
<span class="penncourse-course-notes">Undergraduates Need Permission</span> |
|
https://pennintouchdaemon.apps.upenn.edu/pennInTouchProdDaemon/jsp/fast.do?webService=syllabus&term=2021C&course=CRIM602401 |
|
|
|
CRIM 604-301 |
Criminology in Practice |
Greg Ridgeway |
|
T 03:30 PM-05:30 PM |
|
In this capstone course, students will meet weekly with guests who work on or close to the front line of the criminal justice system. Past guests have included police chiefs, forensic scientists, lobbyists for gun rights and lobbyist for gun control, formerly incarcerated individuals, crime analysts, directors of sentencing commissions, prosecutors and defenders, politicians, and researchers at research organizations working closely with criminal justice agencies. Guests share their career paths, the roles of their organizations in the justice system, and key justice system challenges. Students interact with all guest speakers. |
|
|
|
<span class="penncourse-course-notes">Undergraduates Need Permission</span><br /><span class="penncourse-course-notes">Non-Majors Need Permission From Department</span><br /><span class="penncourse-course-notes">Majors Only</span> |
|
|
|
|
|
CRIM 634-001 |
Evidence-Based Crim Prev |
Aurelie Ouss |
|
W 08:30 AM-11:30 AM |
|
This course considers the use of evidence to identify effective crime prevention policies. The course will teach students to think critically about what constitutes convincing evidence, use benefit-cost analysis in comparing policy alternatives, and write effective policy memos that can translate research into practice. We will develop these skills by studying the effects of different policy approaches to crime prevention including incarceration, policing, gun control, drug regulation, and place-based interventions, as well as education, social programs, and labor market policies. Emphasis will be on the methodological challenges to identifying "what works" and the empirical methods to overcome those challenges. |
|
|
|
|
|
|
|
|
|
CRIM 702-001 |
Math Stat For Crim |
Greg Ridgeway |
|
CANCELED |
|
This is a Ph.D. level course intended to introduce students to advance mathematical statistics methods for development of models and parameter estimation. The main goal is to introduce students to the process of developing likelihood-based models of criminological processes. Examples will draw from racial profiling, police shootings, traffic fatalities. Prerequisites: Single-variable calculus, basic linear algebra, R programming, introductory statistics. |
|
|
|
<span class="penncourse-course-notes">Majors Only</span> |
|
|
|
|
