Jupyter Notebook Analysis of Salary Data Spreadsheet

Re:Jupyter Notebook Analysis of Salary Data Spreadsheet by slashcom on Thursday March 24, 2016 @01:31AM (#11350778)

Most interesting to me was that the gender gap was so much more pronounced in SV than outside

non-SV male median: 97000

non-SV female median: 90000 (92% of male)

SV male median: 137120

SV female median: 99187 (72% of male!)

Unless there's some external factor here, things look pretty damning in SV...

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Re:Jupyter Notebook Analysis of Salary Data Spreadsheet by pedrosorio on Thursday March 24, 2016 @02:33AM (#11350988)

Without looking at the distribution of job_title between male/female in SV and non-SV, these numbers are meaningless.

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Re:Jupyter Notebook Analysis of Salary Data Spreadsheet by Xorlev on Thursday March 24, 2016 @11:29AM (#11353568)

Not to mention, the sample sizes are quite skewed -- the quantiles might line up better with more data.

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