This course will provide the basic mathematical tools and techniques necessary to conduct quantitative empirical research in the social sciences.
We will start by covering probability theory, including random variables, conditional expectation, and conditional expectations. We will examine how these concepts relate to experimentation and inference in social science research. Next, we will focus on the mathematical concepts behind linear regression, including linear algebra and calculus. Finally, we will examine inference for linear regression, introducing bootstrapping and other types of randomization inference.
Throughout the course, we will emphasize the practical applications of these tools and techniques, using real-world examples to help you gain a deeper understanding of the methods you will be applying. By the end of the course, you will have a solid grasp of the fundamental mathematical concepts necessary to conduct quantitative empirical research in the social sciences, as well as the skills needed to apply these concepts effectively.
Overall, this course will provide you with the necessary tools and knowledge to confidently conduct quantitative research in the social sciences, while also emphasizing the importance of understanding the methods you apply.