NSCI 202: Experimental Design & Data Analysis
Prerequisites: NSCI 201 and NSCI 201P recommended.
Restrictions: Instructor permission is required for this course. Use the "Request Course Section Prerequisite Override" task found on your academics dashboard under the Planning ||chr(38)|| Registration section to request this permission.
Offered: Spring
Notes: Can be used for NSCI elective credit (BNS majors). This course is strongly recommended for BNS majors who earned a C or lower in NSCI 201P; students in other majors who desire a more in-depth understanding of the process of research are also welcome. May NOT be taken concurrently with NSCI 203.
This course will use existing data sets to teach students about proper experimental design in the context of different kinds of questions in neuroscience. We will consider the strengths and weaknesses of different techniques and methods in neuroscience and how the choice of experiment design depends upon the hypothesis of the researcher. Students will be given raw data from actual experiments. Together, we will analyze the data using various statistical methods like ttest, ANOVA and MANOVA. Finally, students will learn to effectively graph the results and present them in both written and poster format. There will be two main research projects: one on ligand-receptor interactions and one on a Parkinson’s disease model.