Statistician, data analyst, & quantitative research consultant, PhD

I’m a quantitative research scientist who enjoys forming hypotheses, designing studies to test hypotheses, working with data, building statistical models, conducting statistical tests, and producing fully customized graphs/visualizations to show the results of quantitative research. I also enjoy creating computer simulations and building R Shiny apps. I usually do most of my work in R, though I have also used Stata, Python, Excel, and SPSS in the past. I did a PhD at Stony Brook University, where I conducted quantitative research in political psychology and political economics and where I received extensive training in statistics and methods of data analysis. My coursework included basic statistics and probability, experiment design, econometrics, linear and non-linear regression models (including binomial models, multinomial models, ordered models, count models, censored and truncated models), maximum-likelihood estimation, time-series analysis, experiment design, causal inference, instrumental variables, regression discontinuity, structural equation modeling, factor analysis, game theory, computational modeling and simulations, Bayesian statistics, analysis of big data, automated text analysis, machine learning, and data visualization. For several years I also taught university courses in math, statistics, econometrics, and quantitative research methods for social science. I taught students how to use R, Stata, and Excel for data analysis. I taught both undergraduate students and doctoral students. Please see my website for detailed descriptions of the courses I have taught. I also have experience publishing my own quantitative research in a peer-reviewed journal as a solo author. In my freelance consulting work, I have advised clients on study design and statistical analysis for projects in many different fields of research, including psychology, sociology, economics, linguistics, mental health, medical treatment and recovery, business hiring practices, predictive modeling of asset prices, consumer preferences for market research, and others.