4 ms·

The point of an interactive illustration like this is that it should make it more intuitive and easier to understand than the core concept, not more confusing.

The point of an interactive illustration like this is that it should make it more intuitive and easier to understand than the core concept, not more confusing. What is the meaning of the green and purple lines on the graph, why do they have different gradients and why can't I adjust them? Why does the Simpson's Paradox apply sometimes and not others? Why are there so many bars and donut charts? What does the gray circle around the donuts mean? Information overload.

publicfig 13y ago
I feel as thought both graphs with purple and green lines are accurately explained. Were you trying to skim through the article or were you still left confused after reading it? The top one is explained in the accompanying text and the bottom one is explained with a labeled x and y axis and relies on the information provided above.
- teamonkey 13y ago
  If the article describes the subject adequately, what is the point of the graphic? I found the interactive graphic more confusing than the description. Compare and contrast to the clarity of their central limit theorem demonstation [1] vs its wikipedia page [2]. [1] http://blog.vctr.me/posts/central-limit-theorem.html http://blog.vctr.me/posts/central-limit-theorem.html [2] http://en.wikipedia.org/wiki/Central_limit_theorem http://en.wikipedia.org/wiki/Central_limit_theorem
  - publicfig 13y ago
    By that, I meant that the article described what the graph was representing, not that the article described the information presented adequately. Also, I absolutely disagree with the assumption you made that graphs shouldn't be present if the information is presented in the article. It's good to provide visual demonstrations when applicable in order to help clarify subjects.
jere 13y ago
It took a little playing around to figure out some of the graphics. The donuts indicate which group (men or women) was admitted more in each kind of department. Play around with the sliders and you can see it toggle in the combined row, while simultaneously a yes/no answer updates after the question "Simpson's paradox?" It would really help if yes/no was highlighted. Basically, you can make the paradox appear by dropping the % of women applying to easy departments. You can't make the donut switch in easy or hard departments individually... that's the whole point: women have a slight advantage in each. Honestly, I found the "Proper Pooling" section to have the most intuitive explanation. Combined, there is a bias. By department, there is no bias. The reason is clear: very few women applying to easier departments.
jezebel6 13y ago
Agreed. The text is straightforward enough to understand, but the graphics are irritating and don't contribute much.
ajanuary 13y ago
It doesn't help things aren't labelled very well. I had to fiddle with things to work it all out. But at least I could, which gives it a leg up over an equivalently labelled static graph. In the doughnut charts, blue is accepted rate, red is rejected rate (as labelled earlier in the article). The gray circle indicates which has a higher percentage of acceptance between male and female. The y-axis on the line graph is %age admitted combined over both departments. As you drag the women slider, you'll see the %age accepted rate for women combined over both department matches the y value of the women line in the line chart. The illustration is to show how the distribution of applicants between the easy and hard departments (the lurking explanatory) effects the combined acceptance percentages (the explained). This is the focal point, so all other variables need to be fixed. The fixed values are: in the easy department, 62% of men are accepted and 80% of women are accepted. In the hard department, 26% of men are accepted and 27% of women are accepted. In both departments women are slightly favoured over men, so both always have a gray circle around the women's charts. There are 1,835 women applicants and 1,362 men applicants, making a total of 2,691. The combined accept rates is derived from this static data and the user controlled variable of the distribution of applicants between the departments. You can pick some arbitrary inputs and trace the maths through to calculate how many apply to each department, and how many of those get accepted, then add that up to find the combined value (be warned the actual percentages aren't the nice rounded ones they label them as). While the point on the purple line is below the point on the green line in the y axis, the combined acceptance percentage for women is larger than the men. There is no Simpson's paradox here because taking the lurking explanation into account - that the distribution of applicants between departments has an effect - does not change the outcome. Women are favoured in all three measurements; the gray circle is around all the women's charts. When the point on the purple line is above the point in the green line in the y axis, the combined acceptance percentage for women flips to being smaller than men. Here we have the Simpson's paradox - taking into account the lurking explanation changes the outcome. Women are favoured in the breakdown by department, but men appear favoured in the combined statistic. I found the interactive chart helped me figure out this explanation, but it wasn't helped by poor labelling and the fact they seem to have used real (read messy) statistics to perform the underlying calculations with rather than the nice rounded "62%" etc. they label.
archagon 13y ago
It's a bit confusing, but overall, I really love the presentation of this article. I wish more serious research was presented like this, with lots of knobs for fiddling and experimentation. (See also: Bret Victor.)

publicfig 13y ago

I feel as thought both graphs with purple and green lines are accurately explained. Were you trying to skim through the article or were you still left confused after reading it? The top one is explained in the accompanying text and the bottom one is explained with a labeled x and y axis and relies on the information provided above.

teamonkey 13y ago
If the article describes the subject adequately, what is the point of the graphic? I found the interactive graphic more confusing than the description. Compare and contrast to the clarity of their central limit theorem demonstation [1] vs its wikipedia page [2]. [1] http://blog.vctr.me/posts/central-limit-theorem.html http://blog.vctr.me/posts/central-limit-theorem.html [2] http://en.wikipedia.org/wiki/Central_limit_theorem http://en.wikipedia.org/wiki/Central_limit_theorem
- publicfig 13y ago
  By that, I meant that the article described what the graph was representing, not that the article described the information presented adequately. Also, I absolutely disagree with the assumption you made that graphs shouldn't be present if the information is presented in the article. It's good to provide visual demonstrations when applicable in order to help clarify subjects.

jere 13y ago

It took a little playing around to figure out some of the graphics. The donuts indicate which group (men or women) was admitted more in each kind of department. Play around with the sliders and you can see it toggle in the combined row, while simultaneously a yes/no answer updates after the question "Simpson's paradox?" It would really help if yes/no was highlighted. Basically, you can make the paradox appear by dropping the % of women applying to easy departments. You can't make the donut switch in easy or hard departments individually... that's the whole point: women have a slight advantage in each. Honestly, I found the "Proper Pooling" section to have the most intuitive explanation. Combined, there is a bias. By department, there is no bias. The reason is clear: very few women applying to easier departments.

jezebel6 13y ago

Agreed. The text is straightforward enough to understand, but the graphics are irritating and don't contribute much.

ajanuary 13y ago

It doesn't help things aren't labelled very well. I had to fiddle with things to work it all out. But at least I could, which gives it a leg up over an equivalently labelled static graph. In the doughnut charts, blue is accepted rate, red is rejected rate (as labelled earlier in the article). The gray circle indicates which has a higher percentage of acceptance between male and female. The y-axis on the line graph is %age admitted combined over both departments. As you drag the women slider, you'll see the %age accepted rate for women combined over both department matches the y value of the women line in the line chart. The illustration is to show how the distribution of applicants between the easy and hard departments (the lurking explanatory) effects the combined acceptance percentages (the explained). This is the focal point, so all other variables need to be fixed. The fixed values are: in the easy department, 62% of men are accepted and 80% of women are accepted. In the hard department, 26% of men are accepted and 27% of women are accepted. In both departments women are slightly favoured over men, so both always have a gray circle around the women's charts. There are 1,835 women applicants and 1,362 men applicants, making a total of 2,691. The combined accept rates is derived from this static data and the user controlled variable of the distribution of applicants between the departments. You can pick some arbitrary inputs and trace the maths through to calculate how many apply to each department, and how many of those get accepted, then add that up to find the combined value (be warned the actual percentages aren't the nice rounded ones they label them as). While the point on the purple line is below the point on the green line in the y axis, the combined acceptance percentage for women is larger than the men. There is no Simpson's paradox here because taking the lurking explanation into account - that the distribution of applicants between departments has an effect - does not change the outcome. Women are favoured in all three measurements; the gray circle is around all the women's charts. When the point on the purple line is above the point in the green line in the y axis, the combined acceptance percentage for women flips to being smaller than men. Here we have the Simpson's paradox - taking into account the lurking explanation changes the outcome. Women are favoured in the breakdown by department, but men appear favoured in the combined statistic. I found the interactive chart helped me figure out this explanation, but it wasn't helped by poor labelling and the fact they seem to have used real (read messy) statistics to perform the underlying calculations with rather than the nice rounded "62%" etc. they label.

archagon 13y ago

It's a bit confusing, but overall, I really love the presentation of this article. I wish more serious research was presented like this, with lots of knobs for fiddling and experimentation. (See also: Bret Victor.)