asdfree

analyze survey data for free

awesome-research

:seedling: a curated list of tools to help you with your research/life; I built a front end around this repo, please click on the link

chinese-std-gb-t-7714-related-csl

GB/T 7714相关的csl以及Zotero使用技巧及教程。

clashr_for_windows_chinese

ClashR_for_windows_chinese(ClashR中文版，支持windows）（非原创，From：https://github.com/BoyceLig）

colliderapp

Visualization Collider Effect: ShinyApp

covid_age

COVerAGE-DB: COVID-19 cases, deaths, and tests by age and sex

demographic-methods

Materials for teaching demographic methods

econ379

Program Evaluation for International Development

ginglam

blog

hexo-theme-next

🎉 Elegant and powerful theme for Hexo.

mathstatscode

Codes for my mathematical statistics course

pub_bias

Replication package for Winship and Zhuo (2017)

publishment

replication-material-for-ludwig-bruederl-asr2018

Replication files, Data and Stata Do files for replication of research article: Ludwig, V., & Brüderl, J. (2018). Is There a Male Marital Wage Premium? New Evidence from the United States. American Sociological Review, 83(4), 744–770. https://doi.org/10.1177/0003122418784909

soc4all

Social Survey and Research Methods

socviz

Support files for a data visualization course and book

stat4soc

teaching website

stats-illustrations

R & stats illustrations by @allison_horst

storage

graph

summer-school

南京大学2019年“计算社会科学”论文工作坊

teaching

titanic-machine-learning-from-disaster

Start here if... You're new to data science and machine learning, or looking for a simple intro to the Kaggle prediction competitions. Competition Description The sinking of the RMS Titanic is one of the most infamous shipwrecks in history. On April 15, 1912, during her maiden voyage, the Titanic sank after colliding with an iceberg, killing 1502 out of 2224 passengers and crew. This sensational tragedy shocked the international community and led to better safety regulations for ships. One of the reasons that the shipwreck led to such loss of life was that there were not enough lifeboats for the passengers and crew. Although there was some element of luck involved in surviving the sinking, some groups of people were more likely to survive than others, such as women, children, and the upper-class. In this challenge, we ask you to complete the analysis of what sorts of people were likely to survive. In particular, we ask you to apply the tools of machine learning to predict which passengers survived the tragedy. Practice Skills Binary classification Python and R basics

website

academic website