

Show HN: Sex, politics, and pay gaps in the U.S - akarve
http://www.visualmagnetic.com/html/sex-politics-income/

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anigbrowl
Nice map/presentation, but I fail to see what relationship these metrics are
suppose to have with one another. There' doesn't appear to be a strong
correlation between them and it comes off as rather sophomoric.

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akarve
author here. a more rigorous analysis would include a co-variance matrix and a
best fit line to quantify the relationships between the variables.

on the surface, there doesn't seem to be much of a correlation. not all
exploration reaches a definitive conclusion or even a correlation. the
alternative would be for me to shelve the visualization on the grounds of "no
conclusion". and that would be the file drawer effect in action :)
[http://en.wikipedia.org/wiki/Publication_bias#File_drawer_ef...](http://en.wikipedia.org/wiki/Publication_bias#File_drawer_effect)

~~~
anigbrowl
OK, but what made you pick those three variables to start with? I can see
political leaning vs pay gap, because equal pay legislation/administration is
a somewhat partisan issue. But the length of sexual intercourse measure
doesn't seem to tell us much about anything. Why not measure annual
consumption of corn dogs, or the going price of onions?

I'm open to there being a good reason you chose to include it, but you didn't
offer on on the page so I'm just confused; it reads as a sort of really
abstract titillation, even though it could be interesting to learn what it
_does_ correlate with.

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akarve
i saw nerve.com's data on intercourse duration and started to wonder which
variables might cause or correlate with the same. of greatest interest to me
at the time: how does in/equality affect our sex lives? income is one measure
of equality. politics is a natural third dimension of general interest.

it is a somewhat ad hoc trio of variables, sure, but there's a singular
underlying question: which popular psychographic dimensions affect our sex
lives? given finite time, i picked these 3 and ran with it :)

~~~
anigbrowl
Thanks for taking the time to explain. Although I was critical of that aspect
I thought the design itself was clean and effective, and you should keep
exploring this line of activity.

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minimaxir
Data visualization should be informative and intuitive, at its basest. This is
neither, especially with the distracting, unnecessary animations.

Data visualization can be well designed, yes, but it's not necessary, and it
should definitely not come at _expense_ to ease of interpretation.

~~~
akarve
hi. how would you suggest making it more informative & intuitive, aside from
removing the animations?

~~~
bduerst
What is your purpose in graphing these three metrics at the state level? What
are you trying to communicate?

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couchand
In addition to the criticisms raised by others (the most important of which is
significance!), I'd add that the dots are a poor way to demonstrate the pay
gap. People are notoriously bad at estimating area, particularly when the
variance is so small. The only reason pie charts are acceptable is that you
double encode the metric in area and central angle.

Here you are trying to demonstrate the ratio between two values: the average
pay of women versus men. However, the dimension encoding this metric is
overall area, so the fact that this is a ratio is obscured. Perhaps worse, the
areas are misleading: WY pays its women 37% less than men, yet the dot is
barely visible, far smaller than 63% of the area of the circle (which would be
the intuitive explanation); likewise, it looks (on the scale to the right)
that even 100% pay equality is represented by an incomplete circle.

Also, it looks like you're plotting DC but it's basically impossible to click
on to see the data; for that matter RI, CT and MA are pretty hard to deal
with.

It seems like you're using a force-based layout for the charts, which I take
to mean that the states aren't accurately placed. Please don't move data
points around to suit aesthetic concerns.

Okay, enough negativity, some positives. I quite like the scales to the right.
Some may complain about the animation, but I think that's valuable object
constancy in action. It makes it quite intuitive what's happening when rolling
over the various states. I also like the use of left/right to represent the
political lean.

However: it isn't at all clear where the ends of the scales are and why they
were chosen. The arrowhead makes estimating the length of the political lean
bars difficult. The fact that they are offset by the width of the circle makes
comparison around the middle impossible, and comparison elsewhere hard.

Is this data geographically related? If not, a choropleth is probably not the
right solution. The fact that you're charting state-based data is not enough
to justify a geographical representation.

EDIT: the most important aspect of a data visualization is the message. Don't
just try to make something pretty: think long and hard about what you are
trying to convey. And add text! An explanation is required to make an
interesting visualization comprehensible. If a visualization is completely
understandable without an iota of text, the message is probably entirely
obvious without the visualization.

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verteu
The "pay gap" statistic does not control for occupation, age, or education.
What's the purpose of such an apples-to-oranges comparison?

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tmarthal
If anyone is interested in a similar basic crossfilters written in d3, you can
check out dc.js - [https://github.com/dc-js/dc.js/wiki](https://github.com/dc-
js/dc.js/wiki) (edit: i have no relation to the project, but it's pretty neat)

Here is a list of community contributed examples: [https://github.com/dc-
js/dc.js/wiki#examples-contributed-by-...](https://github.com/dc-
js/dc.js/wiki#examples-contributed-by-community) including some geographic
visualizations.

~~~
couchand
You could also simply work with Crossfilter [0] and D3 [1] directly. They're
both great libraries, and learning their APIs independently seems more
valuable.

[0]:
[http://square.github.io/crossfilter/](http://square.github.io/crossfilter/)

[1]: [http://d3js.org/](http://d3js.org/)

