
How to Read an Unlabeled Sales Chart (2013) - Tomte
https://www.evanmiller.org/how-to-read-an-unlabeled-sales-chart.html
======
axlee
I remember "How Not To Sort By Average Rating" by the same author, which I am
confident helped shape thousands of recommendation/quality sorting algorithms
(including Reddit or Yelp), over the years that followed its writing.

[https://www.evanmiller.org/how-not-to-sort-by-average-
rating...](https://www.evanmiller.org/how-not-to-sort-by-average-rating.html)

~~~
gowld
I doubt it. Evan's algorithm optimizes for user satisfaction. Merchants
optimize for engagement and conversion.

------
Darkphibre
Oh, this is a great read! I fondly recall a meeting with extremely bright
individuals, and several of us were able to deduce the scale on the fly using
the Riemann Zeta Function trick. The presenter was not pleased (the deduced
number was not exactly complimentary to their messaging).

~~~
gowld
How does that work, since in the common case the number of pixels would be
rounded to nearest integer?

The article explains that this only works if you assume that there are much
fewer sales than pixels, so that sales divide pixels.

~~~
Darkphibre
If I remember correctly, the metrics were in millions (and clearly rounded to
the nearest million).

And it wasn't sales data, I believe it had to do with chip design or
marketshare (during the design phase of the current generation of consoles).

------
fyp
> In the absence of calamity, fortuitous events, or brilliant new marketing
> strategies, sale counts are well-described by a Poisson process. That is,
> you can think of there being an underlying average number of sales per day,
> and each day will be a realization of a Poisson distribution with that
> average.

Can someone give a bit more justification for this? It seems like the average
rate shouldn't be constant and is heavily dependent on time/date.

If not, is there another justification for why sales mean should equal sales
variance?

~~~
gowld
> shouldn't be constant and is heavily dependent on time/date.

A priori it is assumed that sales are independent of time. That's part of what
Poisson distribution means -- a constant rate of rolls of a fixed weighted
die. The assumption could be wrong.

> justification for why sales mean should equal sales variance

[https://proofwiki.org/wiki/Variance_of_Poisson_Distribution](https://proofwiki.org/wiki/Variance_of_Poisson_Distribution)

