QTM 110 Introduction to Scientific Methods

Emory College of Art and Science, Emory University

Jiuru Lyu

This is my learning notes of my first year college course QTM 110 at Emory University.

Course Description

QTM 110 is the first course in the sequence of requirements for the Quantitative Sciences (QSS) major; as an introductory course, there are no prerequisites. The course is designed to introduce students to the style of analytic thinking required for research and the concepts and procedures used in the conduct of empirical research. In short, this course teaches a set of skills that are essential for both understanding the research you will encounter in substantive classes, and being able to produce high- quality original research of your own. Beyond simply learning how to be a more critical participant in the academic research community, you will also be better prepared for career opportunities using statistical tools and the products thereof. Whatever the individual career goal, students will learn the principles of critical thinking essential for drawing well-reasoned inferences from data.

The course is organized into four parts. In part one, students will be introduced to the key concept of causality. What is causality and how is it different from correlation? What are common inferential errors you will encounter when presented with research findings? In part two, we examine the “gold standard” of causal inference, experimental empirical research. While an excellent tool for identifying causal empirical relationships, we cannot always use experiments to answer important empirical questions. Part three introduces the alternative, observational empirical data analysis. Critically, we discuss inferential challenges to using observational data, as well as some tools that can help overcome those challenges. Finally, the fourth part covers some topics critical to doing empirical research, whether experimental or observational, including how we can use priors in empirical data analysis, problems of prediction, and modern topics related to presenting research findings.

By the end of this course, students will be able to:

• Define and differentiate types of inference
• Interpret and compare various tools of inference
• Identify inferential problems
• Select appropriate tools for various questions and contexts
• Appraise research questions and applications of tools covered in the course
• Apply patterns of critical thinking presented in the course in order to achieve the above goals