## 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

## 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.

Terms: Aut
| Units: 3

Instructors:
Carroll, G. (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

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

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

Terms: Win
| Units: 5

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

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.

Terms: Spr
| Units: 3-5
| Repeatable for credit

## 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

Instructors:
Jackson, M. (PI)
;
Johnson, A. (TA)

## 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

Instructors:
McFarland, D. (PI)
;
Smith, S. (PI)

## 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

Instructors:
Bagley, S. (PI)
;
Aikens, R. (TA)
;
Antonio, M. (TA)
...
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Instructors:
Bagley, S. (PI)
;
Aikens, R. (TA)
;
Antonio, M. (TA)
;
Ferraro, N. (TA)
;
Kalesinskas, L. (TA)

## 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

Instructors:
Melnikov, O. (PI)
;
Palacios, J. (PI)
;
Cai, F. (TA)
...
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Instructors:
Melnikov, O. (PI)
;
Palacios, J. (PI)
;
Cai, F. (TA)
;
Dey, A. (TA)
;
Fry, K. (TA)
;
Jing, A. (TA)
;
Pavlyshyn, D. (TA)
;
Ray, S. (TA)
;
Ren, Z. (TA)
;
Roquero Gimenez, J. (TA)
;
Seiler, B. (TA)
;
Xu, H. (TA)

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