Quantitative Methods, Causal Inference, and Panel Data
The quantitative method is always my top-priority focus in research. Causal inference is especially interesting for me beyond simple correlation or regression. I recently read two classic books: “Causal Inference in Statistics: A Primer” by Judea Pearl and “Quantitative Social Science: An Introduction” by Kosuke Imai. I regularly write notes about my thoughts and share them here.
- The first step to start reading the two books is to review statistics foundations – “Social Statistics (McGraw-Hill Series in Sociology)” by Hubert M. Blalock and “The Practice of Social Research” by Earl Babbie. (You must have learned Earl’s classic textbook in your college sociology class. Recall it.)
- Distributions, tests, and redefined statistical significance
- Reconsidering observational data and its risks of spurious correlation and endogeneity
- Review: Honestly, these two books are kind of entry-level, not very interesting.