
Why the Normal Distribution Is Vanishing - Futurebot
http://alexdanco.com/2015/12/17/taylor-swift-ios-and-the-access-economy-why-the-normal-distribution-is-vanishing/
======
sz4kerto
This looks bullshit to me. He says the normal distribution is vanishing, and
to prove himself, he brings up some charts which do not look like a normal
distribution. Like the first smartphone-related chart:

"You’re looking to buy a new smartphone. What does your demand distribution
look like? Is it normally distributed? Absolutely not. It looks like this:" [
non-Gaussian 'curve' ]

Okay, what is a 'demand distribution'? I am pretty sure the market demand for
smartphones does not look like the graph he's showing. Etc. etc.

~~~
LoSboccacc
whole article comes only with 'hunches' and not a single data point
researched.

it conveniently ignores many facts and makes up some, like Androids being the
cheaper, low quality choice, ignoring there are devices sold for as much as
iPhones. one could argue that those are sold in lower volumes, but then that'd
be a gaussian distribution

also, of course economics stats are not a good fit for a gaussian. they tend
to stabilize around exponential. that's why the price pyramid is a pyramid.

I have to concede that by looking at some data, it seems there is a
exponential distribution going on for all price ranges except at the highest
end, but that's more a hint of the product price/features space being
discontinuous than we being in a post scarcity society where
gaussian/exponential distributions suddenly vanish.

but anyway, the fact remains that the data is out there, even for the other
field, this on smartphone is but one of the many he didn't research preferring
to follow intuition. and human brain is very bad at applying intuition to
statistics.

[http://image.slidesharecdn.com/tomiahonen-
engagewithmobile-w...](http://image.slidesharecdn.com/tomiahonen-
engagewithmobile-wsa-abudhabi2015-150220083444-conversion-gate01/95/tomi-
ahonen-engage-with-mobile-at-wsamobile-global-congress-abu-
dhabi-38-638.jpg?cb=1424442956)

[http://4.bp.blogspot.com/-uY7kRAl6XfA/URibddfrTqI/AAAAAAAAPL...](http://4.bp.blogspot.com/-uY7kRAl6XfA/URibddfrTqI/AAAAAAAAPLI/pnN9ivxjtt0/s1600/Smartphone+Sales+Distibution+by+ASP.png)

~~~
coldtea
> _it conveniently ignores many facts and makes up some, like Androids being
> the cheaper, low quality choice, ignoring there are devices sold for as much
> as iPhones._

He absolutely does not ignore that fact, in fact he specifically says that the
better end of the market is either iOS or high-end Android phones.

Obviously (and all market data point to that), the Android phones that sell
more are not the high end units, but the cheapo units that dominate the "free
with subscription", "prepaid" etc market.

------
catnaroek
The normal distribution is important because it arises naturally when the
preconditions of the central limit theorem hold. But you still have to use
your brain - you can't unquestioningly assume that any random variable (or
sample or whatever) you will stumble upon will be approximately normally
distributed.

~~~
lordnacho
This is the right answer.

Quite a lot of things are not normally distributed. Often this is because
there's more than one generating mechanism. For instance you may have a
financial market where normally things go up and down smoothly, people are
reacting to news as normal. But then there are also panics, where people are
not behaving normally.

There's also cases where the past influences the future, and drawings are not
identically and independently distributed (though Wikipedia tells me there's
weak variants of the CLT).

~~~
FabHK
The conditions under which the Central Limit Theorem hold are complicated (in
particular, weaker and weaker conditions have been shown to be sufficient even
fairly recently). But intuitively, they boil down to two conditions that are
fairly sensible:

1\. The individual observations can't be _too extreme_. Bounded variance, for
example, is sufficient, but weaker conditions suffice.

2\. The observations must be _somewhat independent_. Independence is a strong
condition and sufficient, but again weaker conditions suffice.

If 1) doesn't hold, a massive outliers could swamp all other observations. If
2) doesn't hold, for example if one underlying factor influences all
observations, all bets are off: the observations could "conspire" to be fairly
large (or fairly small), thus giving rise to fat tails inconsistent with the
normal distribution.

(Having IID (independent identically distributed) observations, btw, is not
sufficient, if the distribution itself is too fat tailed.)

~~~
catnaroek
Nice. I was aware that you could weaken independence, but not bounded
variance. Without bounded variance, I thought you would get something like
Student's t.

------
coldtea
The author is making an observation based on market knowledge and long term
trends.

Yes, he's not mouth-feeding us with the relevant data points -- we can search
for them ourselves and see whether they match his observations or not.

Once we get over this, in the same way that we don't expect any conversation
or comment in real life to come with charts and figures, we can discuss and
try to verify where his assumptions/deductions are correct and whether they
match the data that we have access to.

Being unsubstantiated is a different thing from being wrong.

------
ableal
If anyone else is curious about the second picture, I tineyed (
[http://tineye.com/search/863a041e2607e3405d2dcec1fb148bce471...](http://tineye.com/search/863a041e2607e3405d2dcec1fb148bce4713e8f5/)
;-) it and found two agreeing attributions. One from a 2010 piece by Terry
Tao:

[https://terrytao.wordpress.com/2010/09/14/a-second-draft-
of-...](https://terrytao.wordpress.com/2010/09/14/a-second-draft-of-a-non-
technical-article-on-universality/)

 _' Fig 23. A "living histogram" of 143 students at the University of
Connecticut, with females in white and males in black. (Source: The Hartford
Courant, “Reaching New Heights,” November 23, 1996) Compare this non-bell-
shaped distribution with Figure 5. '_

And another also mentioning U. Connecticut and crediting the photographers in
the image itself:
[http://image.slidesharecdn.com/visualiationofquantitativeinf...](http://image.slidesharecdn.com/visualiationofquantitativeinformation-110321181118-phpapp01/95/visualiation-
of-quantitative-information-39-728.jpg?cb=1300731563)

------
ddebernardy
> The world’s shift from Normal, Gaussian distributions of demand towards
> bifurcated, two-tiered distributions is a natural consequence of our shift
> from a world governed by scarcity to one governed by abundance.

FWIW, others (e.g. Steve Keen, of "Debunking Economics" fame) would
convincingly argue that the world never fit into economist make believe normal
distributions to begin with.

------
metafunctor
This article may look like science, but it's actually just an opinion. Don't
be fooled by the graphs.

------
pjc50
This article hints at the inequality implications, but I think they're likely
to become increasingly important. We're already seeing this with creative
works: the vast majority of works earn zero or near-zero, apart from a few
massive global hits.

Inequality obviously also affects people's ability and willingness to pay for
things. The lower end products are not just cheap but increasingly "free":
either ad-surveillance-supported or paid for by the exploitative gambling-like
"free to play" systems. Again, it's well known in F2P that most of the revenue
comes from a tiny fraction of users.

------
blfr
_This could be a high-end news source like the New York Times; it could also
be a small, niche site like Stratechery._

He's massaging the examples here. Just because NYT is somewhat above the
sewers of the Internet doesn't make it high-end.

There's still a normal distribution with relatively little demand for vile
content (shock sites), more for gossip sites, a lot for Buzzfeed and other
click bait factories, including what fills many Facebook feeds, then less for
NYT and the like, finally very little for niche, truly high quality sources
(blogs run by hobbyists, hackers, professionals, academics).

~~~
coldtea
> _He 's massaging the examples here. Just because NYT is somewhat above the
> sewers of the Internet doesn't make it high-end._

That's beside the point (not to mention that when it comes to perceived
quality, the vast majority of people would call NYT high quality, even if they
don't read it).

The point is most will either go to few specific sources or to a few generic
aggregators, instead of breaking their surfing across a large distribution of
sites (as people did more in mid-nineties).

------
baldfat
Data is wrong on examples.

Mobile Phone = "Good Enough Android" and "iOS and Flagship Android"

[http://www.gartner.com/newsroom/id/2996817](http://www.gartner.com/newsroom/id/2996817)

Apple had 15% of Worldwide phone sales in 2014. Samsung had 24% which is 39%
for both and the sales and demand are fairly similar to what people are
willing to pay. He had data he just didn't want to use.

------
afsina
Author tries to find some anecdotes that would verify his claims, without
actual data of course. I would like to know for example, what is the actual
distribution of money people paying for a cellphone (without contract) in
different countries? Or the distribution of topics that people are looking in
Facebook and elsewhere in Internet. Answer would probably not be a Gaussian
but quite different than what author claims.

------
sageikosa
I was really hoping for something about how marketing identifies consumer
market segments and custom tailors product offerings and prices to make the
best margin they think they can get. Even so, I'd guess that for commoditized
products, there would still be a normalizable distribution of prices offered
within the confines of a targeted market segment.

------
princeb
a single agent's preference might not be normal, but the average agent's
preference is surely asymptotically normal! (as the number of agents tend
towards infinity)

[edit: of course not everything is asymptotically normal. a sequence of
Cauchys do not tend towards the normal distribution.]

