INSH 6500 STATISTICAl ANALYSIS
Northeastern University, Fall 2023, Spring 2024
This course is specifically designed as an introductory course in probability and statistics, tailored to meet the needs of graduate students in the College of Social Sciences and Humanities (CSSH). The primary goal of this course is to provide students with a strong foundation in regression and generalized linear models, which will be extensively examined in INSH 7500 or an equivalent advanced statistics course. To achieve this objective, the course will cover a broad range of topics: the fundamental concepts of probability theory, the properties of random variables, asymptotic approximations, statistical estimators, hypothesis testing, and causal inference. In order to provide hands-on experience and practical skills, the course will incorporate statistical computing using R. Students will have the opportunity to gain proficiency in utilizing R as a statistical tool, enabling them to manipulate, analyze, and visualize data effectively.
POLS 2400 QUANTITATIVE TECHNIQUES
Northeastern University, Spring 2023
This class is an intro-level course of quantitative methods in Political Science to introduce students how political ‘scientists’ see and leverage data to understand human behaviors and society. The primary purpose of this course is to build on statistical basics and develop data analytic skills including how to describe data, draw inferences from samples to population, set up hypotheses, and test them based on data in experimental and observational research.
POLITSC 7552 QUANTITATIVE POLITICAL ANALYSIS II
Ohio State University, Spring 2022
This course is doctoral-level course of quantitative methods to learn a family of the linear and generalized linear modeling using maximum likelihood estimation (MLE) and Bayesian estimation. The primary purpose of the course is to build on statistical foundations taught in PoliSci 7551. We will perform regression analysis with the following types of outcome variables: continuous, counts, dichotomous outcomes, ordered categorical outcomes, unordered categorical outcomes, bounded variables, and multilevel variables.