Cognition and Aging Research Lab

Bryn Mawr College


Introduction to Data Science, DSCI B100
“Data science” is a catch-all term used to describe the practice of working with and analyzing messy data to draw meaningful conclusions using techniques developed by computer scientists and computational statisticians. This course provides a broad introduction to the field of data science via the statistical programming language, R.

Research Methods and Statistics, PSYC B205
This course will provide an overview of experimental design, general research methodology, and the analysis and interpretation of data. Topics include descriptive and inferential statistics, experimental design and validity, analysis of variance, and correlation and regression. The primary objective of this course is to provide students with a toolkit that they can use to become a more sophisticated and critical consumer and producer of statistical information. Lecture three hours, laboratory 90 minutes a week.

Human Cognition, PSYC B212
This course provides an overview of the field of Cognitive Psychology, the branch of psychology that studies how we acquire, store, process and communicate information. We will survey classic and contemporary theories and findings about what the human mind is, how it evolved, how it accomplishes the extraordinary achievements necessary for day-to-day living, and what happens when something goes wrong. Our goal over the semester is to understand how the human mind works!

Laboratory in Cognitive Psychology, PSYC B282
This laboratory course will provide hands-on experience in designing and conducting research in cognitive psychology, with an emphasis on the study of memory and cognition. Over the semester, students will have the opportunity to develop specific research skills, such as understanding how to design a study appropriate to a research question, collecting data, conducting and interpreting statistical analyses, writing about research, etc. Students will be exposed to behavioral and electrophysiological (EEG, ERP) techniques to study memory and cognition. The course will culminate with a final project in which students design and conduct a novel experiment, analyze the data, and prepare an APA style research report. This class is a writing intensive class and, as a .5 unit class, is designed to meet half of the writing requirement in the major.

Data Science with R: PSYC B318
This is an advanced data science seminar course. The course focuses on using computational methods and statistical techniques to analyze massive amounts of data and to extract knowledge. It provides an overview of tools for data acquisition and cleaning, data manipulation, data analysis and evaluation, visualization and communication of results, data management and big data systems. The course surveys the complete data science process from data to knowledge and gives students hands-on experience with tools and methods. Prerequisites: PSYC B205, PSYC H200, or SOCL B265. Students with good statistical preparation in math or other disciplines should consult with the instructor to gain permission to take the class.

Advanced Topics in Cognitive Neuroscience: The Emotional Brain, PSYC B323
This is a seminar course dealing with the emerging field of affective neuroscience and its intersection with cognition, psychophysiology and neuroscience. The goal of the course is to review and critically examine current theories and research on emotions and the neurobiological systems that underpin them. We will examine the behaviors and brain circuits (anatomy, connectivity, and function) involved in the perception and experience of emotions and emotional stimuli and the influence of emotional stimuli on cognitive processing.

Faculty Research Assistant, INDT B410
This course creates opportunities for students to work on faculty research performing a variety of tasks. Students in this course will assist with ongoing research projects using a combination of traditional behavioral methods and/or brain wave (EEG/ERP) methods. Responsibilities will include scheduling and running participants, coding and cleaning up data in Excel or SPSS, and depending on their interests, students will also have the opportunity to gain hands-on experience analyzing data and coding experiments using software such as Excel, SPSS, E-Prime, R, and Matlab. Students should expect to work 4-6 hours per week. Qualifications: Applicants should be enthusiastic, organized, conscientious, and comfortable interacting with people of all ages, and in a team environment.