Im not sure if i understand it correctly, but minimum wage in lithuania is around 5,2 eur/h before taxes and 3,9 eur/h after taxes

Yeah, I’m curious too. I wouldn’t have expected Colorado to be bad exactly… but tied with Massachusetts, home to Harvard, MIT, and many other colleges, is surprising.

You should post this in r/Australia, a lot of people would have a mental breakdown over this data.

It's not really a beautiful visualization though. At least to me it looks confusing and visually bland. Is there any reason for the column colors, or is it just your choice?

Statistically if you average it out, you should reduce bias. But, it won't eliminate the same. Also, such data is not available at a global scale.

Yeah it's difficult to notice that

Does this take into account hours worked? Quality of work? Age? Etc

Follow-up to the previous post ( ILO data visualized using Datawrapper)

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That’s not what it means or what people who say it are talking about.

It might be what you’ve wrongly thought they mean, but that’s all on you and Dr Peterson

Most people understand it. You and the others who think it’s an attack on men clearly don’t

"Intel" being connected with "syndrome" is kind of funny

Damn it feels good (for South Carolina) to be one point ahead of notorious blue blood Iowa Pre-Flight. But it's hilarious that several other SEC teams can't say that.

It is the case that women are getting more degrees than men at present, but as shown by Pew the pay gap continues relatively steadily.

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Aha, that's good to know, otherwise, just visually it gives the impression that the wealthier the country the larger the gap is. Whereas the ordering shows there is no such correlation.

The graph's x-axis is just the funds sorted in order of their values, right? That fact that that's not the kind of x-axis that you can label and draw points on should indicate to you that the visualization is not ideal.

I think in your title assertion you're confusing "power law" with the "long tail". To verify this relationship you will need an actual x-y plot. The way to get there, from what you are describing, is with binning.

As others have pointed out something like a power law should be on a log-scale graph. When you do bins in an example like this you definitely want to try putting it on a log-log graph. But if you're not sure what you're looking for or demonstrating, you should output both log- and linear-scale graphs for your viewer.

In the Netherlands, one of the reasons the gap is so high because many women chose to work part-time after they start a family. Due to the strong family orientation of the culture, that option is available.

That has two implications:

• They work less days (my wife works 2 days, for example).
• They are usually ineligible for more senior people manager roles due to only logging on for part of the week.

i've lived in both korea and malaysia and i can tell you without a doubt that koreans waste much more food.

Koreans have a side dish culture which literally goes straight to the waste bin if not eaten by customers.

Malaysia have prominent a la carte dishes culture that produces less waste in general

I really doubt the data

Haha you again saying that no one understands “gender pay gap”….glad you have your own understanding of words unique to yourself

Woah you got me there….

Nope not confused at all….typically when people reference the “pay gap” they are insinuating that women get paid less than men for the exact same job (which would lead to companies hiring only women). They are also insinuating that it stems from sexism and/or bigotry towards women….that is also false.

Literally no one ever has denied the pay gap of lump averages by gender….the question is why

the only "real" minimum wage is 0

I’m scratching my head at Michigan, the winningest team in college football, being the lowest ranked team on this infographic

You don’t seem to understand what the term gender pay gap describes