I am highlighting the differences in Male and Female HDR's in Africa, to explore the relationship that the HDR and male and female GDI's have with the economic growth of the country, to find out if the nature of the relationship is causal or effect.
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This project visualizes a comparison in GDI (female and male) scores to the economic status to prove its influence on the gender gap of each country in Africa.
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My hypothesis is that the economic status has a large influence over the gender gap. The lower the status, the larger the gap is between men and women.
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The visualization shows a locational relationship between country and overall HDR score, as well as a more specific view of the economic status as well as the factors that make up the HDR score for both men and women.
- Sources include the dataset from 3.2, containing the HDI breakdown which includes GDI and information used to create that score as well as the GDP ranking provided by World Bank.
I am visualizing the gender gap in Africa, highlighting the differences between the HDR scores of different genders and the other scores that influence the HDR, to gain an understanding of the gaps that do exists and the factors that effect them.
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This project visualizes a comparison in GDI (female and male) scores to prove the gender gap of each country in Africa.
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I believe that there is a large gender gap in most African countries.
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The visualization compares the GDI for each gender and country, providing evidence of a gender gap. Filtering options will provide a more specific view of the factors that make up the HDR score for both men and women.
- Sources include the dataset from 3.2, containing the HDI breakdown which includes GDI and information used to create that score. I would like to include the GDI over time, but it is unavailable at the moment.