[Phys-L] data visualization; snowfall example; 3He example

[John Denker <jsd@av8n.com>]

In the context of http://apod.nasa.gov/apod/ap160125.html
on 01/26/2016 11:13 AM, Aburr@aol.com wrote:

> A nit which can be picked is the suggestion that 
> Tc should have a split source coloring because all of that element  which 
> is used is man made.

I wouldn't even split it. The title of the diagram is
"Where Your Elements Came From" and for all practical 
purposes all of "my" technetium is man-made.  Similar
words apply to neptunium and plutonium, contrary to
what is shown in the diagram.

Still, nevertheless:

> A very useful and interesting link.

Let's talk about what makes it useful and interesting.

My point for today has to do with /data visualization/.  Note
the contrast:
 -- IMHO it would be mildly interesting to simply dig up 
  the raw nucleosynthesis data.
 ++ The data becomes much more interesting and (for some purposes)
  more useful when it is plotted on a color-coded periodic table.

This is a Really Big Deal.  This is a lesson that everybody
(students and professionals alike) should take to heart.  Having
the numbers is not good enough;  you have to /understand/ the
numbers.

Here's another example, a famous example of why it's important
to visualize the data in real time, while the experiment is still
underway.  It has to do with the discovery of superfluid 3He:
  https://www.av8n.com/physics/data-visualization.htm#sec-3he

Here's yet another example.  Over the weekend I was talking
with someone who moved from Maine to suburban Virginia.  She
said the amount of snow dropped by the Snowzilla storm was
/more/ than what she was accustomed to seeing in Maine.

That sounded interesting, so I decided to look into it.  I found
a newspaper article that had data for the max 24-hour snowfall
on a state-by-state basis.  However, it was infuriating, because
it was formatted as a flip-book, with one data point per page.
There was no way to see more than one data pint at once, hence
no way to make comparisons.  So ... I tracked down some raw data 
and plotted it in a couple of interesting ways:
  https://www.av8n.com/physics/data-visualization.htm#sec-snowfall

I find it a bit surprising that by this measure, Arizona and New 
Mexico are snowier than Idaho, North Dakota, Minnesota, and Michigan.
Also, South Dakota ranks much higher than North Dakota.

Remember that this is max snowfall in a single 24-hour period; it
is not snow per storm, and certainly not snow per season.

===========================
Here are some useful general principles:

  1.  It pays to visualize the data. Having the numbers is not 
   good enough; you have to /understand/ the numbers.
  2.  It pays to visualize the data while the experiment is 
   still underway. It allows you to catch mistakes, and it 
   allows you to make serendipitous discoveries. It might lead
   you into new avenues of research.
  3. It pays to look at the data in more than one way. Sorting
   the data alphabetically serves some purposes, while sorting it
   numerically serves other purposes. Try spreading the data out
   in one dimension, then try spreading it out in two dimensions,
   et cetera. Look at it from many different angles.
  4. You don’t necessarily know in advance the best way(s) of
    visualizing the data. So follow Pólya’s famous advice: Try 
    something; if that doesn’t suffice, try something else.
  5. This rewards cleverness and creativity. Two people who do 
   the same experiment ought to get the same numbers ... but
   they might not visualize the numbers in the same way. Therefore 
   they might achieve different levels of understanding.