Experimental Design & Data Analysis

4.0 credits

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.