## Quantitative Methods Courses

The bulk of my teaching focuses on the required courses in quantitative methods at the undergraduate and graduate levels. This includes:

### SOCY 2061 Introduction to Social Statistics

A significant amount of sociological research uses quantitative methods (e.g., statistical analyses) to investigate social phenomena. These researchers use large national surveys, public opinion polls, and census data to document, describe, and explain a wide range of sociologically motivated research questions. As students of this body of research, it is important to have a basic understanding of statistics if one is to be an active participant in the local, regional, national, and international dialog within the sociological community. The primary goal of this class is to provide each student with the requisite skills to not only understand the mainstream sociological research but also to be critical consumers of statistical information that is often presented as “factual”. Although the primary emphasis is on social research, the information and skills that you will learn in this class will be applicable to most academic and non-academic careers. The course is divided into three sections that focus on descriptive statistics and inferential statistics and various applied statistical techniques. Descriptive statistics are methods that allow you to present a set of scores in a parsimonious summary form that measure individual and social characteristics (e.g., socioeconomic status, self-esteem, residential segregation). The primary concepts that we emphasize are central tendency (e.g., mean, mode, median) and dispersion (e.g., standard deviation, variance, inter-quartile range). Inferential Statistics is the backbone of statistical reasoning and it involves making estimates about a population (e.g., the entire country) based on a sample (e.g., a random selection of people from the country). This process necessarily involves the invocation of the basic rules of probability and it will introduce you to hypothesis testing which is used throughout the physical, behavioral, and social sciences. We will also cover bivariate and multivariate statistical techniques in great detail and you will have an opportunity to examine data using the statistical software R. We will use data from the 2018 General Social Survey, described in detail here.

### SOCY 5111 Data 1

At the end of this course students should a) demonstrate mastery of fundamental concepts of inferential statistics; b) be able to use STATA to read and manage data sources, c) be able to use STATA to perform univariate, bivariate, and introductory multivariate analyses; d) be able to write about the methods used and the results obtained in the analyses in part C. This class sets the foundation for more advanced statistical analyses in Data 2 and it is a critical component of your graduate training in sociology. When you are finished with this class, you should have the requisite tools to do original empirical research on your own using existing quantitative data sources.

### SOCY 6111 Data 2

The primary objective of this course is to cover, review, and extend the basic linear model to deal with outcomes that are common in sociology. The emphasis is on the empirical application of different statistical techniques, as well as training students to be educated consumers of some advanced quantitative methods used in sociological research. This means gaining a comprehensive understanding of: 1) the assumptions of different modeling strategies; 2) what different modeling strategies can do and, equally important; 3) what different modeling strategies cannot do. The beginning of this course will focus on ordinary least squares regression, which forms the basis of most other quantitative techniques. This course will also cover generalized linear modeling approaches to binary, ordinal, and count dependent variables, as well as basic introductions into multilevel modeling approaches. This class is designed as a survey course that provides a strong, but introductory, foundation for advanced quantitative techniques. Accordingly, students should not expect to leave this course as “experts” in any singular modeling strategy but should continue to read and develop their skills after the course is over.

### Undergraduate Training

I have also contributed to the training of the social science undergraduate students in the key components of sociological approaches to health. I developed an undergraduate course entitled Social Epidemiology which has become an important course in the undergraduate public health certificate program on the CU Boulder campus.

### SOCY 3032 Social Epidemiology

Epidemiology is the study of the distribution of and determinants of states of health in the population. Epidemiologic research has long focused on aspects of the built and social environment that increase the risk of exposure of particular diseases and affect the duration and severity of exposure. However, the explicit emphasis on the proximate determinants of disease inadvertently overlooks the fundamental role played by the broad social patterning of health, health behaviors, access to health care, and exposure to health risks. Some refer to these ‘upstream’ risks as ‘fundamental causes’ of health and illness in populations. The social epidemiologic perspective has several key tenets: (1) epidemiology is best studied from a population rather than individual perspective; (2) risks are clustered within discrete social places such as neighborhoods, schools, and workplaces; (3) a lifecourse perspective is critical to the understanding of the pathology of a particular disease; and (4) sensitivity and resilience are characteristics of individuals but also characteristics of social places. Readings are primarily drawn from Social Epidemiology but we will supplement with current social epidemiological research papers. The course will also have an applied component in which we will apply the theories that we discuss in class to current empirical data. This does not require any background in statistics, computer programming, or mathematics beyond basic algebra.