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COMM 318: Quantitative Social Science Research Methods

An introduction to a broad range of social science research methods that are widely used in PhD work. Prerequisite: consent of instructor.
Terms: Spr | Units: 1-5 | Grading: Letter or Credit/No Credit
Instructors: ; Krosnick, J. (PI)

COMM 339: Questionnaire Design for Surveys and Laboratory Experiments: Social and Cognitive Perspectives (POLISCI 421K, PSYCH 231)

The social and psychological processes involved in asking and answering questions via questionnaires for the social sciences; optimizing questionnaire design; open versus closed questions; rating versus ranking; rating scale length and point labeling; acquiescence response bias; don't-know response options; response choice order effects; question order effects; social desirability response bias; attitude and behavior recall; and introspective accounts of the causes of thoughts and actions.
Terms: Aut | Units: 4 | Grading: Letter or Credit/No Credit
Instructors: ; Krosnick, J. (PI)

DESINST 215: The Design of Data

Our world is increasingly complex and laden with many forms of measurable data. Infographics abound, but whether explicit or not, the stories they tell are all designed. In this hyper-concentrated, hands-on course, students will learn to use mapping and design techniques to sort and synthesize data, unlock insights and communicate information. We will create four different types of maps and infographics and students will practice finding insight from both qualitative and quantitative information. Take this course if you are interested in learning how to navigate through and create for the complicated intersection of data and design.nnAdmission by application. See dschool.stanford.edu/classesn for more information.
Terms: Spr | Units: 3-4 | Grading: Letter or Credit/No Credit

ECON 292: Quantitative Methods for Empirical Research

This is an advanced course on quantitative methods for empirical research. Students are expected to have taken a course in linear models before. In this course I will discuss modern econometric methods for nonlinear models, including maximum likelihood and generalized method of moments. The emphasis will be on how these methods are used in sophisticated empirical work in social sciences. Special topics include discrete choice models and methods for estimating treatment effects.
Terms: Aut | Units: 2-5 | Grading: Letter or Credit/No Credit
Instructors: ; Imbens, G. (PI)

EDUC 200A: Introduction to Data Analysis and Interpretation

Primarily for master's students in the School of Education. Focus is on reading literature and interpreting descriptive and inferential statistics, especially those commonly found in education. Topics: basic research design, instrument reliability and validity, descriptive statistics, correlation, t-tests, one-way analysis of variance, and simple and multiple regression. All offerings of this course (whether meeting on Mon & Weds or Tues & Thurs) will be taught identically.
Terms: Aut | Units: 4 | Grading: Letter or Credit/No Credit

EDUC 200B: Introduction to Qualitative Research Methods

(Formerly EDUC 151.) Primarily for master's students: An introduction to the core concepts and methods of qualitative research. Through a variety of hands-on learning activities, readings, field experiences, class lectures, and discussions, students will explore the processes and products of qualitative inquiry.nnThis is a graduate level course. No undergraduates may enroll. Priority will be given to GSE students, and final enrollment depends on instructor approval after the first day of class.
Terms: Aut, Win | Units: 4 | Grading: Letter or Credit/No Credit

EDUC 260B: Advanced Statistical Methods for Observational Studies (CHPR 266, HRP 292, STATS 266)

Design principles and statistical methods for observational studies. Topics include: matching methods, sensitivity analysis, and instrumental variables. 3 unit registration requires a small project and presentation. Computing is in R. Pre-requisites: HRP 261 and 262 or STATS 209 (HRP 239), or equivalent. See http://rogosateaching.com/somgen290/
Terms: Spr | Units: 2-3 | Grading: Medical Option (Med-Ltr-CR/NC)

EDUC 278: Introduction to Issues in Evaluation

Open to master's and doctoral students with priority to students in the School of Education. Focus is on the basic literature and major theoretical and practical issues in the field of program evaluation. Topics include: defining purpose, obtaining credible evidence, the role of the evaluator, working with stakeholder, values in evaluation, utilization, and professional standards. The course project is to design an evaluation for a complex national or international program selected by the instructor.
Terms: Spr | Units: 3-4 | Grading: Letter or Credit/No Credit
Instructors: ; Ruiz-Primo, M. (PI)

EDUC 292: Academic Writing for Clarity and Grace

Students will acquire helpful writing strategies, habits, and critical faculties; increase their sense of writing as revision; and leave them with resources that will support them in their own lifelong pursuit of good writing. Students will work on revising their own papers and editing papers of other students. Class will focus on exercises in a variety of critical writing skills: framing, concision, clarity, emphasis, rhythm, action, actors, argument, data, quotations, and usage. Course enrollment limited to graduate students.
Terms: Win | Units: 2-4 | Grading: Satisfactory/No Credit
Instructors: ; Jordan, Z. (PI)

EDUC 326: Advanced Regression Analysis

Social science researchers often deal with complex data and research questions that traditional statistics models like linear regression cannot adequately address. This course offers the opportunity to understand and apply two widely used types of advanced regression analysis that allow the examination of 1) multilevel data structures (multilevel models) and 2) multivariate research questions (structural equation models).
Terms: Spr | Units: 3-5 | Grading: Letter or Credit/No Credit
Instructors: ; Smith, S. (PI)

EDUC 334A: Youth and Education Law Project: Clinical Practice

(Same as LAW 660A). The Youth and Education Law Project offers students the opportunity to participate in a wide variety of educational rights and reform work, including direct representation of youth and families in special education and school discipline matters, community outreach and education, school reform litigation, and/or policy research and advocacy. All students have an opportunity to represent elementary and high school students with disabilities in special education proceedings, to represent students in school discipline proceedings, or to work with community groups in advocating for the provision of better and more equitable educational opportunities to their children. In addition, the clinic may pursue a specific policy research and advocacy project that will result in a written policy brief and policy proposal. Students working on special education matters have the opportunity to handle all aspects of their clients' cases. Students working in this area interview and counsel clients, investigate and develop facts, work with medical and mental health professionals and experts, conduct legal and educational research, create case plans, and represent clients at individual education program (IEP) team meetings, mediation or special education due process hearings. This work offers students a chance to study the relationship between individual special education advocacy and system-wide reform efforts such as impact litigation. Students working on school discipline matters interview and counsel clients, investigate and develop facts, interview witnesses, conduct legal and educational research, create case plan, and represent clients at school discipline hearings such as expulsion hearings. Such hearings provide the opportunity to present oral and written argument, examine witnesses, and present evidence before a hearing officer. If appropriate and necessary, such proceedings also present the opportunity to represent students on appeal before the school district board of trustees or the county board of education. The education clinic includes two or three mandatory training sessions to be held at the beginning of the term, a weekly seminar that focuses on legal skills and issues in law and education policy, regular case review, and a one hour weekly meeting with the clinic instructor. Admission is by consent of instructor. Beginning with the 2009-2010 academic year, each of the Law School's clinical courses is being offered on a full-time basis for 12 credits.
Terms: Win, Spr | Units: 4 | Grading: Letter or Credit/No Credit
Instructors: ; Koski, W. (PI)

EDUC 334B: Youth and Education Law Project: Clinical Methods

(Same as LAW 660B). The Youth and Education Law Project offers students the opportunity to participate in a wide variety of educational rights and reform work, including direct representation of youth and families in special education and school discipline matters, community outreach and education, school reform litigation, and/or policy research and advocacy. All students have an opportunity to represent elementary and high school students with disabilities in special education proceedings, to represent students in school discipline proceedings, or to work with community groups in advocating for the provision of better and more equitable educational opportunities to their children. In addition, the clinic may pursue a specific policy research and advocacy project that will result in a written policy brief and policy proposal. Students working on special education matters have the opportunity to handle all aspects of their clients' cases. Students working in this area interview and counsel clients, investigate and develop facts, work with medical and mental health professionals and experts, conduct legal and educational research, create case plans, and represent clients at individual education program (IEP) team meetings, mediation, or special education due process hearings. This work offers students a chance to study the relationship between individual special education advocacy and system-wide reform efforts such as impact litigation. Students working on school discipline matters interview and counsel clients, investigate and develop facts, interview witnesses, conduct legal and educational research, create case plan, and represent clients at school discipline hearings such as expulsion hearings. Such hearings provide the opportunity to present oral and written argument, examine witnesses, and present evidence before a hearing officer. If appropriate and necessary, such proceedings also present the opportunity to represent students on appeal before the school district board of trustees of the county board of education. The education clinic includes two or three mandatory training sessions to be held at the beginning of the term, a weekly seminar that focuses on legal skills and issues in law and education policy, regular case review, and a one hour weekly meeting with the clinic instructor. Admission is by consent of instructor. Beginning with the 2009-2010 academic year, each of the Law School's clinical courses is being offered on a full-time basis for 12 credits.
Terms: Win, Spr | Units: 4 | Grading: Letter or Credit/No Credit
Instructors: ; Koski, W. (PI)

EDUC 339: Advanced Topics in Quantitative Policy Analysis

For doctoral students. How to develop a researchable question and research design, identify data sources, construct conceptual frameworks, and interpret empirical results. Presentation by student participants and scholars in the field. May be repeated for credit.
Terms: Aut, Win, Spr | Units: 1-2 | Repeatable for credit | Grading: Satisfactory/No Credit

EDUC 347: The Economics of Higher Education

(Same as GSBGEN 348) Topics: the worth of college and graduate degrees, and the utilization of highly educated graduates; faculty labor markets, careers, and workload; costs and pricing; discounting, merit aid, and access to higher education; sponsored research; academic medical centers; and technology and productivity. Emphasis is on theoretical frameworks, policy matters, and the concept of higher education as a public good. Stratification by gender, race, and social class.
Terms: Win | Units: 3-4 | Grading: Letter or Credit/No Credit
Instructors: ; Bettinger, E. (PI)

EDUC 399A: Designing Surveys

This workshop/course is designed for students who are designing a survey for use in a research project. The workshop content draws on relevant cognitive processing theories and research (on comprehension, retrieval, judgment, and reporting). In addition to some readings and a few lectures, this workshop is designed to be highly interactive and practical. By the end of the course students will have designed and pilot tested their survey instrument. Course may be repeated for credit.
Terms: Win | Units: 1-2 | Repeatable for credit | Grading: Satisfactory/No Credit
Instructors: ; Porteus, A. (PI)

EDUC 401A: Mini Courses in Methodology: Statistical Packages for the Social Sciences (SPSS)

Statistical analysis using SPSS, including generating descriptive statistics, drawing graphs, calculating correlation coefficients, conducting t-tests, analysis of variance, and linear regression. Building up datasets, preparing datasets for analysis, conducting statistical analysis, and interpreting results.
Terms: Aut | Units: 1 | Grading: Satisfactory/No Credit
Instructors: ; Lang, D. (PI)

EDUC 401B: Mini Courses in Methodology: Stata

The goal of this course is to familiarize students with the Stata statistical software package for use in quantitative research. By the end of the course, students should be able to import and export data, clean and manage data, conduct standard statistical tests (e.g., correlation, t-test, regression), and produce a graph.
Terms: Aut, Win | Units: 1 | Grading: Satisfactory/No Credit
Instructors: ; Stenhaug, B. (PI)

EDUC 401D: Multilevel Modeling Using R (STATS 196A)

See http://rogosateaching.com/stat196/ . Multilevel data analysis examples using R. Topics include: two-level nested data, growth curve modeling, generalized linear models for counts and categorical data, nonlinear models, three-level analyses. Class meets April 8, April 15, April 22, April 29, May 13.
Terms: Spr | Units: 1 | Grading: Satisfactory/No Credit
Instructors: ; Rogosa, D. (PI)

EDUC 423: Introduction to Data Science (EDUC 143, SOC 302)

Social scientists can benefit greatly from utilizing new data sources like electronic administration records or digital communications, but they require tools and techniques to make sense of their scope and complexity. This course offers the opportunity to understand and apply popular data science techniques regarding data visualization, data reduction and data analysis.
Terms: Win | Units: 3-5 | Grading: Letter or Credit/No Credit

EDUC 430C: Using Data to Describe the World: Descriptive Social Science Research Techniques (SOC 258C)

Course provides hands-on practice in analysis of data from experimental and quasi-experimental research designs, including a) instrumental variables estimators; b) regression discontinuity estimators; c) difference-in-difference estimators; d) matching estimators; e) fixed effects estimators; and f) panel data methods (including individual fixed effects models, lagged covariate adjustment models, growth models, etc.). Prerequisites: satisfactory completion of EDUC 255B, EDUC 257C, or SOC 257. May be repeat for credit
Terms: Spr | Units: 3-5 | Repeatable for credit | Grading: Letter (ABCD/NP)
Instructors: ; reardon, s. (PI)

EDUC 450C: Qualitative Interviewing

Addressing the theoretical underpinnings of qualitative interviews as well as the application of theory to practice, this course considers different approaches to interviewing. Interview types covered will range from group interviews to individual interviews, and from unstructured, ethnographically oriented interviews to highly structured interviews. Working with community partners to facilitate application to practice, the students will move from theory to interview design, implementation, and initial stages of analysis, with an emphasis on consistency in approach and utility in graduate-level research.
Terms: Win | Units: 3 | Repeatable for credit | Grading: Letter or Credit/No Credit
Instructors: ; Ardoin, N. (PI)

EFSLANG 683R: Workshop in Reading and Vocabulary for International Students

(1-2 units). Provides support in the development of English reading skills for academic purposes, including work on comprehension, speed, and critical interpretation, along with strategies for improving vocabulary. Students taking the course for 2 units will have additional individual assignments and a 50-minute tutorial each week. Limited to visiting undergraduates and students in the High School Summer College program.
Terms: Sum | Units: 1-2 | Grading: Satisfactory/No Credit
Instructors: ; QUIJANO, L. (PI)

EFSLANG 683S: Workshop in Oral Communication for International Students

(1-2 units) Provides support in the development of listening and speaking skills in English, including academic listening, small group discussion, oral presentation, and intercultural communication. Students taking the course for 2 units will have additional individual assignments and a 50-minute tutorial each week. Limited to visiting undergraduates and students in the High School Summer College program.
Terms: Sum | Units: 1-2 | Grading: Satisfactory/No Credit

EFSLANG 683W: Workshop in Written Communication for International Students

(1-2 units). Provides support in the development of English writing skills for non-natives. Writing assignments are negotiated with the instructor and may include practice in composition, SAT or TOEFL writing, and writing university application essays and statements of purpose. Students taking the course for 2 units will have additional individual assignments and a 50-minute tutorial each week. Limited to visiting undergraduates and students in the High School Summer College program.
Terms: Sum | Units: 1-2 | Grading: Satisfactory/No Credit
Instructors: ; QUIJANO, L. (PI)

EFSLANG 688: Intensive English and Academic Orientation for Foreign Graduate Students

Goal is to prepare incoming international graduate students for full-time study. Academic orientation and instruction in academic writing, listening, discussion, oral presentation, and spoken usage. Enrollment limited to 14. Course may be repeated once.
Terms: Sum | Units: 6 | Repeatable for credit | Grading: Satisfactory/No Credit

EFSLANG 688A: Intensive Spoken English

For current graduate students. Includes work on listening, oral presentation, discussion, and conversational interaction. May fulfill any two of the following EFS requirements, subject to approval by the EFS Director: EFSLANG 690A, 690B, 691, 693B.
Terms: Sum | Units: 3 | Grading: Satisfactory/No Credit

EFSLANG 688B: Intensive Academic Writing

For current graduate students. Focus on academic writing, with some work in reading and vocabulary development. Engineering, science, humanities, and social science students prepare a research paper; business students write one or more case studies. Fulfills requirement for EFSLANG 697 or 698A, subject to approval by the EFSLANG Director.
Terms: Sum | Units: 3 | Grading: Satisfactory/No Credit

EFSLANG 689P: Pronunciation

The sounds of English, and stress, intonation, and rhythm patterns important to natural-sounding speech. Enrollment limited to 14.
Terms: Sum | Units: 1 | Repeatable for credit | Grading: Satisfactory/No Credit
Instructors: ; Wang, D. (PI)

EFSLANG 690A: Interacting in English

Strategies for communicating effectively in social and academic settings. Informal and formal language used in campus settings, including starting and maintaining conversations, asking questions, making complaints, and contributing ideas and opinions. Simulations and discussions, with feedback on pronunciation, grammar, and usage. Enrollment limited to 14.
Terms: Aut, Win, Spr | Units: 1-3 | Grading: Satisfactory/No Credit
Instructors: ; Geda, K. (PI); Wang, D. (PI)

EFSLANG 690B: Academic Discussion

Skills for effective participation in classroom settings, seminars, and research group meetings. Pronunciation, grammar, and appropriateness for specific tasks. Feedback on language and communication style. Enrollment limited to 14. May be repeated once for credit. Prerequisite: EFSLANG 690A or consent of instructor.
Terms: Aut, Win, Spr | Units: 1-3 | Repeatable for credit | Grading: Satisfactory/No Credit

EFSLANG 690C: Advanced Interacting in English

Communication skills for extended discourse such as storytelling and presenting supported arguments. Development of interactive listening facility and overall intelligibility and accuracy. Goal is advanced fluency in classroom, professional and social settings. Identification of and attention to individual patterned errors. May be repeated once for credit. Prerequisite: EFSLANG 690B or consent of instructor. Enrollment limited to 14.
Terms: Win, Spr | Units: 1-3 | Repeatable for credit | Grading: Satisfactory/No Credit
Instructors: ; Streichler, S. (PI)

EFSLANG 691: Oral Presentation

For advanced graduate students. Practice in academic presentation skills; strategy, design, organization, and use of visual aids. Focus is on improving fluency and delivery style, with videotaping for feedback on language accuracy and usage. Enrollment limited to 14. May be repeated once for credit.
Terms: Aut, Win, Spr | Units: 1-3 | Repeatable for credit | Grading: Satisfactory/No Credit

EFSLANG 691S: Oral Presentation

For advanced graduate students. Practice in academic presentation skills; strategy, design, organization, and use of visual aids. Focus is on improving fluency and delivery style, with video recording for feedback on language accuracy and usage. Fulfills the requirement for EFSLANG 691.
Terms: Sum | Units: 2 | Grading: Satisfactory/No Credit
Instructors: ; Streichler, S. (PI)

EFSLANG 693A: Listening Comprehension

Strategies for effective listening in an academic setting, focusing on identifying key ideas in lectures. Practice in understanding words and phrases commonly encountered in classroom settings. Computer-based exercises for comprehension of rapid, natural speech. Enrollment limited to 14.
Terms: Aut | Units: 1-3 | Grading: Satisfactory/No Credit
Instructors: ; Lockwood, R. (PI)

EFSLANG 693B: Advanced Listening Comprehension, and Vocabulary Development

Listening strategies and vocabulary for understanding English in academic and non-academic contexts. Discussion and interpretation of communicative intent. Computer-based and video exercises across a range of genres; individual project. May be repeated once for credit. Prerequisite: EFSLANG 693A or consent of instructor.
Terms: Aut, Win, Spr | Units: 1-3 | Repeatable for credit | Grading: Satisfactory/No Credit

EFSLANG 695A: Pronunciation and Intonation

Recognition and practice of American English sounds, stress, and intonation patterns for greater comprehension and intelligibility. Analysis of problem areas. Biweekly tape assignments and tutorials. May be repeated once for credit. Enrollment limted to 14.
Terms: Aut, Win, Spr | Units: 1-3 | Repeatable for credit | Grading: Satisfactory/No Credit

EFSLANG 695B: Advanced Pronunciation and Intonation

Continuation of EFSLANG 695A, focusing on American English sounds, stress, rhythm, and intonation patterns. Emphasis is on self-monitoring, integrated with short presentations. Biweekly tape assignments and tutorials. Enrollment limited to 14. May be repeated for credit three times. Prerequisite: EFSLANG 695A.
Terms: Aut, Win | Units: 1-3 | Repeatable for credit | Grading: Satisfactory/No Credit
Instructors: ; Wang, D. (PI)

EFSLANG 697: Gateway to Graduate Writing

Focus is on improving grammatical accuracy and vocabulary, building fluency, and learning the structure and conventions of English correspondence, reports, and short academic papers. Enrollment limited to 14.
Terms: Aut, Win, Spr | Units: 1-3 | Grading: Satisfactory/No Credit
Instructors: ; Geda, K. (PI)

EFSLANG 698A: Writing Academic English

Strategies and conventions for graduate writing. Emphasis is on fluency, organization, documentation, and appropriateness for writing tasks required in course work. Enrollment limited to 14. May be repeated once for credit.
Terms: Aut, Win, Spr | Units: 1-3 | Repeatable for credit | Grading: Satisfactory/No Credit

EFSLANG 698B: Advanced Graduate Writing

Focus on clarity, accuracy, and appropriate style. For graduate students experienced in English writing and currently required to write for courses and research. Class meetings and individual conferences. Prerequisite: EFSLANG 698A. Enrollment limited to 14. May be repeated once for credit.
Terms: Aut, Win, Spr | Units: 1-3 | Repeatable for credit | Grading: Satisfactory/No Credit

EFSLANG 698C: Writing and Presenting Research

For advanced graduate students completing major research projects. Revising and editing strategies for preparing papers, conference abstracts, and poster presentations. Practice adapting written and oral presentational content and style to different audiences. Students present their research and receive instructor and peer feedback, with regular individual tutorials in addition to class work. Enrollment limited to 12. May be repeated twice for credit. Prerequisite: Students required by the EFS Placement Exam to take EFSLANG 691, 697, 698A, or 698B may not enroll in 698C until those requirements have been fulfilled. Others may sign up directly.
Terms: Win | Units: 1-3 | Repeatable for credit | Grading: Satisfactory/No Credit
Instructors: ; Hubbard, P. (PI)

EFSLANG 698S: Writing Academic English

Strategies and conventions for graduate writing. Emphasis is on fluency, organization, documentation, and appropriateness for writing tasks required in course work and in producing research papers. Fulfills the requirement for EFSLANG 698A.
Terms: Sum | Units: 2 | Grading: Satisfactory/No Credit
Instructors: ; Streichler, S. (PI)

ENGR 202W: Technical Communication

This course focuses on how to write clear, concise, and organized technical writing. Through interactive presentations, group workshops, and individual conferences, students learn best practices for communicating to academic and professional audiences for a range of purposes.
Terms: Aut, Win, Spr | Units: 3 | Grading: Letter (ABCD/NP)

ETHICSOC 278M: Introduction to Environmental Ethics (ETHICSOC 178M, PHIL 178M, PHIL 278M, POLISCI 134L)

How should human beings relate to the natural world? Do we have moral obligations toward non-human animals and other parts of nature? And what do we owe to other human beings, including future generations, with respect to the environment? The first part of this course will examine such questions in light of some of our current ethical theories: considering what those theories suggest regarding the extent and nature of our environmental obligations; and also whether reflection on such obligations can prove informative about the adequacy of our ethical theories. In the second part of the course, we will use the tools that we have acquired to tackle various ethical questions that confront us in our dealings with the natural world, looking at subjects such as: animal rights; conservation; economic approaches to the environment; access to and control over natural resources; environmental justice and pollution; climate change; technology and the environment; and environmental activism.
Terms: Spr | Units: 4-5 | Grading: Letter (ABCD/NP)
Instructors: ; Adams, M. (PI)

HRP 206: Meta-research: Appraising Research Findings, Bias, and Meta-analysis (CHPR 206, MED 206, STATS 211)

Open to graduate, medical, and undergraduate students. Appraisal of the quality and credibility of research findings; evaluation of sources of bias. Meta-analysis as a quantitative (statistical) method for combining results of independent studies. Examples from medicine, epidemiology, genomics, ecology, social/behavioral sciences, education. Collaborative analyses. Project involving generation of a meta-research project or reworking and evaluation of an existing published meta-analysis. Prerequisite: knowledge of basic statistics.
Terms: Win | Units: 3 | Grading: Medical Satisfactory/No Credit

HRP 223: Introduction to Data Management and Analysis in SAS

Provides hands-on introduction to basic data management and analysis techniques using SAS. Data management topics include: Introduction to SAS and SAS syntax, importing data, creating and reading SAS datasets, data cleaning and validation, creating new variables, and combining data sets. Analysis techniques include: basic descriptive statistics (e.g., means, frequency) and bivariate procedures for continuous and categorical variables (e.g., t-tests, chi-squares).
Terms: Aut | Units: 2 | Grading: Medical Satisfactory/No Credit
Instructors: ; Park, L. (PI); Popat, R. (PI)

HRP 237: Practical Approaches to Global Health Research (INTLPOL 290, MED 226)

(Formerly IPS 290) How do you come up with an idea for a useful research project in a low resource setting? How do you develop a research question, prepare a concept note, and get your project funded? How do you manage personnel in the field, complex cultural situations, and unexpected problems? How do you create a sampling strategy, select a study design, and ensure ethical conduct with human subjects? This course takes students through the process of health research in under-resourced countries from the development of the initial research question and literature review to securing support and detailed planning for field work. Students progressively develop and receive weekly feedback on a concept note to support a funding proposal addressing a research question of their choosing. Aimed at graduate students interested in global health research, though students of all disciplines interested in practical methods for research are welcome. Undergraduates who have completed 85 units or more may enroll with instructor consent.
Terms: Win | Units: 1-3 | Grading: Medical Option (Med-Ltr-CR/NC)
Instructors: ; Luby, S. (PI)

HRP 244: Developing Measurement Tools for Health Research

The focus of this course is on providing the skills necessary to develop, validate and administer both qualitative and quantitative measures and instruments. Topics will include creating valid measures, ensuring the measures used address and apply to the research questions, design and samples; determining when to use standardized measures or develop new ones; instrument validation techniques; factor analysis; and survey administration, including determining the most effective way of administering measures (e.g., online, paper-and-pencil, ACASI) and the best way to design the survey.
Terms: Win | Units: 2 | Grading: Medical Option (Med-Ltr-CR/NC)
Instructors: ; Halpern-Felsher, B. (PI)

HRP 264: Foundations of Statistical and Scientific Inference (STATS 264)

The course will consist of readings and discussion of foundational papers and book sections in the domains of statistical and scientific inference. Topics to be covered include philosophy of science, interpretations of probability, Bayesian and frequentist approaches to statistical inference and current controversies about the proper use of p-values and research reproducibility. nnRecommended preparation: At least 2 quarters of biostatistics and one of epidemiology. Intended for second year Masters students, of PhD students with as least 1 year of preceding graduate training.
Terms: Aut | Units: 1 | Grading: Medical Satisfactory/No Credit
Instructors: ; Goodman, S. (PI)

MGTECON 383: Measuring Impact in Business and Social Enterprise

This class provides students with practical skills for measuring impact in business and social enterprise. How large is the impact of raising prices on sales? Is an advertising campaign working? Does a non-profit actually improve people's lives? Students will finish the course with the ability to design, analyze, and skeptically evaluate experiments that can rigorously answer questions like these. Students will learn: how to evaluate claims of causality; how to conduct and analyze experiments and quasi-experiments; the advantages and disadvantages of experiments; how to quantify uncertainty; and what can go wrong in experiments. Students will acquire a conceptual understanding of basic experimental statistics to inform these skills. Students will also be exposed to how leading companies, researchers, and social innovators strategically deploy experiments. Finally, students will conduct their own experiments on a topic of their choosing in small groups. The class will not assume any prior experience or training with statistics, math or R. However, completing short problem sets and participation in weekly lab sessions will entail acquiring basic knowledge of R.
Units: 3 | Grading: GSB Letter Graded
Instructors: ; Broockman, D. (PI)

NBIO 227: Understanding Techniques in Neuroscience

Students will learn to select and evaluate multidisciplinary techniques for approaching modern neuroscience questions. A combination of lectures and small group paper discussions will introduce techniques from molecular, genetic, behavioral, electrophysiological, imaging, and computational neuroscience. Students will be expected to complete homework assignments analyzing primary literature and attend optional laboratory demonstrations. Intended for graduate students, postdocs, and staff from any discipline; and for advanced undergraduates in the biosciences, engineering, or medicine.
Terms: Aut | Units: 2 | Grading: Medical Satisfactory/No Credit

OB 670: Designing Social Research

This is a course in the design of social research, with a particular emphasis on research field (i.e., non-laboratory) settings. As such, the course is a forum for discussing and developing an understanding of the different strategies social theorists employ to explain social processes, develop theories, and make these theories as believable as possible. In general, these issues will be discussed in the context of sociological research on organizations, but this will not be the exclusive focus of the course. A range of topics will be covered, for example: formulating and motivating research questions; varieties of explanation; experimental and quasi-experimental methods, including natural experiments; counterfactual models; conceptualization and measurement; sampling and case selection; qualitative and quantitative approaches. This course is particularly oriented toward developing an appreciation of the tradeoffs of different approaches. It is well suited to Ph.D. students working on qualifying papers and dissertation proposals.
Units: 3 | Grading: GSB Letter Graded
Instructors: ; Carroll, G. (PI)

ORALCOMM 219: Oral Communication for Graduate Students

(Formerly CTL 219.) Graduate student speaking activities such as teaching (delivering lectures, guiding discussion, and facilitating small groups), professional presentations and conference papers, and preparing for oral exams and defenses. In-class projects, discussion, and individual evaluation assist students in developing effective techniques for improving oral communication skills.
Terms: Sum | Units: 1-2 | Grading: Letter or Credit/No Credit
Instructors: ; Allen, D. (PI)

POLISCI 421K: Questionnaire Design for Surveys and Laboratory Experiments: Social and Cognitive Perspectives (COMM 339, PSYCH 231)

The social and psychological processes involved in asking and answering questions via questionnaires for the social sciences; optimizing questionnaire design; open versus closed questions; rating versus ranking; rating scale length and point labeling; acquiescence response bias; don't-know response options; response choice order effects; question order effects; social desirability response bias; attitude and behavior recall; and introspective accounts of the causes of thoughts and actions.
Terms: Aut | Units: 4 | Grading: Letter or Credit/No Credit
Instructors: ; Krosnick, J. (PI)

PSYCH 231: Questionnaire Design for Surveys and Laboratory Experiments: Social and Cognitive Perspectives (COMM 339, POLISCI 421K)

The social and psychological processes involved in asking and answering questions via questionnaires for the social sciences; optimizing questionnaire design; open versus closed questions; rating versus ranking; rating scale length and point labeling; acquiescence response bias; don't-know response options; response choice order effects; question order effects; social desirability response bias; attitude and behavior recall; and introspective accounts of the causes of thoughts and actions.
Terms: Aut | Units: 4 | Grading: Letter or Credit/No Credit
Instructors: ; Krosnick, J. (PI)

PSYCH 252: Statistical Methods for Behavioral and Social Sciences

This course offers an introduction to advanced topics in statistics with the focus of understanding data in the behavioral and social sciences. It is a practical course in which learning statistical concepts and building models in R go hand in hand. The course is organized into three parts: In the first part, we will learn how to visualize, wrangle, and simulate data in R. In the second part, we will cover topics in frequentist statistics (such as multiple regression, logistic regression, and mixed effects models) using the general linear model as an organizing framework. We will learn how to compare models using simulation methods such as bootstrapping and cross-validation. In the third part, we will focus on Bayesian data analysis as an alternative framework for answering statistical questions.
Terms: Win | Units: 5 | Grading: Letter or Credit/No Credit
Instructors: ; Gerstenberg, T. (PI)

SOC 258C: Using Data to Describe the World: Descriptive Social Science Research Techniques (EDUC 430C)

Course provides hands-on practice in analysis of data from experimental and quasi-experimental research designs, including a) instrumental variables estimators; b) regression discontinuity estimators; c) difference-in-difference estimators; d) matching estimators; e) fixed effects estimators; and f) panel data methods (including individual fixed effects models, lagged covariate adjustment models, growth models, etc.). Prerequisites: satisfactory completion of EDUC 255B, EDUC 257C, or SOC 257. May be repeat for credit
Terms: Spr | Units: 3-5 | Repeatable for credit | Grading: Letter (ABCD/NP)
Instructors: ; reardon, s. (PI)

SOC 280B: Introduction to Data Analysis (CSRE 180B, SOC 180B)

Methods for analyzing and evaluating quantitative data in sociological research. Students will be taught how to run and interpret multivariate regressions, how to test hypotheses, and how to read and critique published data analyses.
Terms: Spr | Units: 4 | Grading: Letter (ABCD/NP)
Instructors: ; Jackson, M. (PI)

SOC 302: Introduction to Data Science (EDUC 143, EDUC 423)

Social scientists can benefit greatly from utilizing new data sources like electronic administration records or digital communications, but they require tools and techniques to make sense of their scope and complexity. This course offers the opportunity to understand and apply popular data science techniques regarding data visualization, data reduction and data analysis.
Terms: Win | Units: 3-5 | Grading: Letter or Credit/No Credit

SOMGEN 223: Introduction to R for data analysis

Introduction to R, an open-source programming language for statistical computing and graphics. Topics include: the basics of the R language and RStudio environment, data inspection and manipulation, graphics for data visualization, and tools for reproducible research. Interactive format combining lecture and hands-on computer lab, with time to work on your own data. Numerous in-class and homework exercises to build effective skills. Examples will be drawn from different areas of biology and medicine.
Terms: Aut, Win, Spr | Units: 3 | Grading: Medical Option (Med-Ltr-CR/NC)
Instructors: ; Bagley, S. (PI)

STATS 200: Introduction to Statistical Inference

Modern statistical concepts and procedures derived from a mathematical framework. Statistical inference, decision theory; point and interval estimation, tests of hypotheses; Neyman-Pearson theory. Bayesian analysis; maximum likelihood, large sample theory. Prerequisite: STATS 116.
Terms: Aut, Win | Units: 3 | Grading: Letter or Credit/No Credit

STATS 202: Data Mining and Analysis

Data mining is used to discover patterns and relationships in data. Emphasis is on large complex data sets such as those in very large databases or through web mining. Topics: decision trees, association rules, clustering, case based methods, and data visualization. Prereqs: Introductory courses in statistics or probability (e.g., Stats 60), linear algebra (e.g., Math 51), and computer programming (e.g., CS 105).
Terms: Aut, Sum | Units: 3 | Grading: Letter or Credit/No Credit
Instructors: ; Walther, G. (PI)

STATS 203: Introduction to Regression Models and Analysis of Variance

Modeling and interpretation of observational and experimental data using linear and nonlinear regression methods. Model building and selection methods. Multivariable analysis. Fixed and random effects models. Experimental design. Prerequisites: a post-calculus introductory probability course, e.g. STATS 116. In addition, a co-requisite post-calculus mathematical statistics course, e.g. STATS 200, basic computer programming knowledge, and some familiarity with matrix algebra.
Terms: Win | Units: 3 | Grading: Letter or Credit/No Credit
Instructors: ; Siegmund, D. (PI)

STATS 203V: Introduction to Regression Models and Analysis of Variance

Modeling and interpretation of observational and experimental data using linear and nonlinear regression methods. Model building and selection methods. Multivariable analysis. Fixed and random effects models. Experimental design. This course is offered remotely only via video segments (MOOC style). TAs will host remote weekly office hours using an online platform such as Zoom. Prerequisites: a post-calculus introductory probability course, e.g. STATS 116. In addition, a co-requisite post-calculus mathematical statistics course, e.g. STATS 200, basic computer programming knowledge, and some familiarity with matrix algebra.
Terms: Sum | Units: 3 | Grading: Letter or Credit/No Credit
Instructors: ; Kaluwa Devage, P. (PI)

STATS 204: Sampling

How best to take data and where to sample it. Examples include surveys and sampling from data warehouses. Emphasis is on methods for finite populations. Topics: simple random sampling, stratified sampling, cluster sampling, ratio and regression estimators, two stage sampling.
Terms: Spr | Units: 3 | Grading: Letter or Credit/No Credit
Instructors: ; Basse, G. (PI)

STATS 211: Meta-research: Appraising Research Findings, Bias, and Meta-analysis (CHPR 206, HRP 206, MED 206)

Open to graduate, medical, and undergraduate students. Appraisal of the quality and credibility of research findings; evaluation of sources of bias. Meta-analysis as a quantitative (statistical) method for combining results of independent studies. Examples from medicine, epidemiology, genomics, ecology, social/behavioral sciences, education. Collaborative analyses. Project involving generation of a meta-research project or reworking and evaluation of an existing published meta-analysis. Prerequisite: knowledge of basic statistics.
Terms: Win | Units: 3 | Grading: Medical Satisfactory/No Credit

STATS 290: Computing for Data Science

Programming and computing techniques for the requirements of data science: acquisition and organization of data; visualization, modelling and inference for scientific applications; presentation and interactive communication of results. Emphasis on computing for substantial projects. Software development with emphasis on R, plus other key software tools. Prerequisites: Programming experience including familiarity with R; computing at least at the level of CS 106; statistics at the level of STATS 110 or 141.
Terms: Win | Units: 3 | Grading: Letter or Credit/No Credit
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