Year: 2017
Type: article
Abstract: This course concerns the logic of causal inference in social science research.We can gain knowledge about the world by applying the scientific method, but there are many pitfalls in how we use experiments and observation to make inferences about cause and effect relationships.This class will primarily focus on those pitfalls, and how experiments can be designed to minimize errors in our inference.Although this class may cover some basic principles of using statistics and how to decide on experimental sample sizes (power analyses), it is not intended to be a statistics or data analysis course.Instead, the aim is to convey the logic behind research methods, and the different problems that can limit conclusions when using these tools.More than anything else, this class is designed to help prepare you for your own research projects.While we will be covering the ideas presented in the textbook, the primary emphasis will be to make progress on preparing you for your own specific research projects.Many of you will be starting this course without a concrete research plan, but now is the time to develop one.By the end of the class you will be expected to have drafted a written proposal of your research (for many of you, this will be your Master's project) and to present these to your classmates.
Source: The Mathematics Enthusiast
Author: Nathan Insel
Language: English
Subfield: Education
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W2761270249