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CDAD-UH 1043EQ Data and Society | Fall 2021 | Final Project

HTML 99.27% Jupyter Notebook 0.71% TeX 0.01%
causal-inference confounder linear-regression r-language data-visualization

violence-against-women's Introduction

Violence-Against-Women

CDAD-UH 1043EQ Data and Society | Fall 2021 | Final Project

"The aim of this project is to understand how social/political/economic factors are associated with the OECD’s Violence Against Women data. Our primary data source comes from a 2019 OECD study of violence against women using three indicators (attitudes, laws and experience of violence)."

Data Source

  1. 2019 OECD study of violence against women (attitudes, laws and experience of violence): https://data.oecd.org/inequality/violence-against-women.htm#indicator-chart

  2. The World Bank Alcohol Consumption: https://data.worldbank.org/indicator/SH.ALC.PCAP.LI

  3. The World Bank Poverty Headcount: https://data.worldbank.org/indicator/SI.POV.NAHC

  4. Country-Continent data: https://wzb-ipi.github.io/corona/df_full.csv

Report

The report was written using Rmarkdown.

report.rmd contains all the codes for the analysis. Please knit the file and check the HTML output. If knitting the Rmarkdown does not work for some reason, please check report.html. It was the output I had last time. If this doesn't work either, please check presentations&report/Report.pdf.

You will probably get a different output of the causal graph every time you knit the report, so please refer to this one where the lables do not overlap.

causal

violence-against-women's People

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