Results for VPGE::Specialized

An introduction to a broad range of social science research methods that are widely used in PhD work. Prerequisite: consent of instructor.

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.

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.

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.

(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. This 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.

This course is designed with the belief that collecting information is a routine activity in which most researchers and educators are involved. Developing and improving instruments to gather information for descriptive, assessment, research, or evaluation purposes is a goal that unites all social sciences. Therefore, this course focuses on the technical skills required to develop, judge, and/or select quality instruments in diverse domains. The course will focus on your personal journey to develop or judge an instrument on something that is important for you.

Concepts of reliability and validity; derivation and use of test scales and norms; mathematical models and procedures for test validation, scoring, and interpretation.

This course will cover the material from EDUC 252 in an applied setting. Emphasis will be in developing a capacity for applying and interpreting psychometrics techniques to real-world and simulated data.

See http://rogosateaching.com/stat209/. Application of potential outcomes formulation for causal inference to research settings including: mediation, compliance adjustments, time-1 time-2 designs, encouragement designs, heterogeneous treatment effects, aggregated data, instrumental variables, analysis of covariance regression adjustments, and implementations of matching methods. Prerequisite: an introduction to causal inference methods such as STATS209.

Major periods of evolution, particularly since the mid-19th century. Premise: insights into contemporary higher education can be obtained through its antecedents, particularly regarding issues of governance, mission, access, curriculum, and the changing organization of colleges and universities.

The purpose of Introduction to Program Evaluation (EDUC 278) is to provide an introduction to the field of program evaluation. Students taking this course will learn basic concepts and participate in intellectual debates in the field. This course is intended to examine issues and challenges faced by evaluators of educational and social programs. We will be working with real evaluation tasks throughout the course. The class will meet once a week for 2hrs 50 min. It is critical that you commit to reading all the material before class, so that the discussion is well-focused. During the last weeks of the course, an evaluation proposal of a real-world program will be developed. The proposal will become the final paper.

In this workshop style course, you will learn principles for effective writing in graduate education and beyond. Beginning with consideration of the inherited and cultivated traditions informing your writing practices, you will examine the processes that best support your development as a writer; apply key rhetorical principles to your own writing and analyze those principles at work in other people's prose; practice writing about texts for a variety of purposes; and use feedback to revise your writing for both disciplinary-specific and public audiences. Master's students who are drafting a thesis and doctoral students who are working on qualifying papers or dissertations are especially encouraged to enroll.

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).

(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.

(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.

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.

(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.

We examine unprecedented scrutiny and critiques of US colleges and universities. How have expectations changed? How have campus leaders and faculty responded? Who is served, what is taught, what research is prioritized, and what public impact is envisioned-contributing to democracy via access, education for citizenship and employment, producing reliable knowledge, serving as a community partner. Sources are readings, group work, and speakers. The seminar is designed for graduate students across the university. Undergraduates and postdocs need the instructor's permission.

American higher education has had to continually struggle with issues of difference, particularly racial and ethnic cultural difference, throughout its history. While the civil rights and student protest era of the 1960s are easily recognized as moments of cultural struggle, they evolve and take new forms, extending and re-framing ideological and material conflict in the academy. These include battles over: the content of the curriculum; access to college and admissions; and the domains of legitimate knowledge. In this course, we will critically examine and discuss the research and discourse concerning issues of diversity and equity in the current era. We will examine the political, cultural, and social contours of these issues and as well as the efficacy of campus responses to them such as race-conscious admissions policies, identity-based offices, ethnic studies programs, and other DEI (diversity, equity, and inclusion) initiatives.

This workshop/course is designed for students who are designing a survey to collect quantitative data for a research project. The workshop content draws on relevant cognitive processing theories and research related to development of good survey questions. In addition to some readings and a few mini 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 enrollment is limited to 12 students and may be repeated for credit.

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.

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.

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.

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.

This course focuses on the skills needed to conduct theoretically-informed and policy-relevant descriptive social science. Students read recent examples of rigorous descriptive quantitative research that exemplifies the use of data to describe important phenomena related to educational and social inequality. The course will help develop skills necessary to conceptualize, operationalize, and communicate descriptive research, including techniques related to measurement and measurement error, data harmonization, data reduction, and visualization. Students develop a descriptive project during the course. Prerequisite: satisfactory completion of a course in multivariate regression.

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. 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.

(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.

(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.

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.

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.

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 Coordinator: EFSLANG 690A, 690B, 691, 693B.

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 coordinator.

The sounds of English, and stress, intonation, and rhythm patterns important to natural-sounding speech.

Building vocabulary for academic success. Idiomatic language, and what idioms and metaphors reflect about American culture. Enrollment limited to 14.

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.

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. May be repeated once for credit. Prerequisite: EFSLANG 690A or consent of instructor.

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.nhttps://language.stanford.edu/programs/efs/l

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. May be repeated once for credit.

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.

This course focuses on strategies for effective listening to university lectures and other academic content, such as seminars and group discussions. It extends beyond listening for main ideas and details, providing practice in identifying discourse markers common in academic settings and in recognizing and accommodating implied information, hesitations, and reduced forms, such as contractions. It also covers challenging areas such as processing numbers and adapting to unfamiliar vocabulary. Listening practice is complemented by instruction in effective note-taking and study strategies to retain and review comprehended information. Additionally, the course has a significant discussion component, giving students the opportunity to interpret what they hear to develop a deeper and more critical understanding of the content and to link that understanding to their own spoken English production and interaction. Materials include recorded lectures from Stanford faculty and other relevant sources.

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.

This course provides training in recognizing and practicing American English sounds, stress, and intonation patterns in connected speech in order to improve comprehension and enhance intelligibility in a variety of settings. After receiving an individualized analysis of speech patterns, students engage in directed practice both with online software and in class, receiving immediate feedback. Through these in-class activities and practice assignments, students will improve their ability to pronounce English clearly and to self-monitor and self-correct. The instructor will meet with students regularly throughout the quarter for one-on-one tutorials. Enrollment limited to 12.

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.

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. Fulfills the requirement for EFSLANG 695A.

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.

Strategies and conventions for graduate writing. Emphasis is on fluency, organization, documentation, and appropriateness for writing tasks required in course work. May be repeated once for credit.

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. May be repeated once for credit.

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.

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.

To be effective as an engineer or scientist, you must communicate your cutting-edge research and projects effectively to a broad range of audiences: your professors, your fellow students, your colleagues in the field, and sometimes the public. ENGR. 202W offers a collaborative environment in which you will hone your communication skills by writing and presenting about a project of your choosing and working on your CV/resume. ENGR202W is a practicum (supervised practical application) that helps you build toward a complete skillset for technical communication in the twenty-first century. Through interactive presentations and activities, group workshops, and individual conferences, you will learn best practices for communicating to academic and professional audiences for a range of purposes.

How should human beings interact with 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? In this course, we will tackle 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. We will frame our inquiry with leading ethical theories and divide our approach to these topics by ecosystem, dedicating time to each unique environment and its specific nuances: aquatic, desert/tundra, forest/grassland, and the increasingly recognized environment of Space.

Stanford graduates will play important roles in solving many of today's and tomorrow's major societal problems-in areas such as education, health, energy, and domestic and global poverty-that call for actions by nonprofit, business, and hybrid organizations as well as governments. This course teaches skills and bodies of knowledge relevant to these roles, covering topics such as designing, implementing, scaling, and evaluating social strategies; systems thinking; decision making under risk; psychological biases that adversely affect people's decisions; methods for influencing behavior; and pay-for-success programs. The large majority of the course will be devoted to students' working in teams to apply these concepts and tools to an actual problem, with teams choosing whatever problem interests them.

Businesses are increasingly expected to have a positive social impact, as evidenced by the rapid growth of impact investing. Yet, even as the impact investing market has taken off, impact measurement has lagged, undermining the credibility of the sector. Impact measurement is also critical to individual firms, not-for-profits and governments, as they face increased pressure to generate quantifiable results. How can we measure impact? What are some of the most effective frameworks, tools and approaches for impact measurement? How does one choose the most appropriate measurement tool based on factors such as the size, maturity and sector of an organization? Can impact be distilled down to a single monetary measure, such as a dollar? These and other questions will be explored in considerable depth, through analysis and discussion of case studies as well as hand-on use of impact measurement tools. This course is a good match for students interested in impact measurement, impact investing, profit-with-purpose businesses or the role of business in society. The course will be co-taught by Matt Bannick, who led the impact investing firm, Omidyar Network, and served as the President of PayPal and of eBay International, and Neil Malhotra, Director of the Center for Social Innovation and an expert in the statistical measurement of impact.

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.

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.

(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.

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.

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.

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. Please view course website: https://psych252.github.io/. Open to graduate students only. Requirement: Psych 10/Stats 60 or equivalent

This course focuses on the skills needed to conduct theoretically-informed and policy-relevant descriptive social science. Students read recent examples of rigorous descriptive quantitative research that exemplifies the use of data to describe important phenomena related to educational and social inequality. The course will help develop skills necessary to conceptualize, operationalize, and communicate descriptive research, including techniques related to measurement and measurement error, data harmonization, data reduction, and visualization. Students develop a descriptive project during the course. Prerequisite: satisfactory completion of a course in multivariate regression.

Preference to sociology majors, minors, and co-terms. 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.

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.

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. Please note that students must enroll in one section in addition to the main lecture.

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). May not be taken for credit by students with credit in STATS 216 or 216V.

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, basic computer programming knowledge, some familiarity with matrix algebra, and a pre- or co-requisite post-calculus mathematical statistics course, e.g. STATS 200.

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, basic computer programming knowledge, some familiarity with matrix algebra, and a pre- or co-requisite post-calculus mathematical statistics course, e.g. STATS 200.

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.

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.

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.