Graduate coursework often covers either foundational statistics or dives deep into a single method — but rarely offers a broad map of the quantitative and computational landscape. To fill that gap, my cohort and I have been studying different research methods together, exploring both statistics and computational social science. The learning topics are partly inspired by the ICPSR Summer Program in Quantitative Methods and the Summer Institute in Computational Social Science (SICSS).

This site is an AI-organized learning notebook for me. Each method includes key concepts and an article example, with the goal of building a first understanding of when and how each method is used. For deeper knowledge, further study is needed.

研究生课程通常只涵盖基础统计或深入某一个方法——但很少提供定量与计算方法的全景地图。为了弥补这个空白，我和同学们一起学习不同的研究方法，探索统计学和计算社会科学。学习主题的灵感部分来自 ICPSR 定量方法暑期项目和计算社会科学暑期学院（SICSS）。

这个网站是AI为我整理的学习笔记本。每种方法包含核心概念和文章示例，目标是建立对每种方法何时使用、如何使用的初步理解。更深入的知识需要进一步学习。