Welcome Back. I’ve Been Waiting…
If you’re reading this, then chances are you also read Part 1, “Probability for Game Designers.”
If
you haven’t read it, you really should, and that’s not to say it is
full of good stuff (the article is tripe, actually). I just recommend
reading it because if you don’t, you might be unprepared for the
silliness that may ensue during this serious *ahem* and erudite *cough*
discussion of statistics.
This article focuses on a
few select statistical topics that I believe should be understood by
game designers. In particular, statistics really is useful and
important for system designers, mechanicians, balancers, and other
subclasses of designer that are usually relegated to steerage.
Disclaimer taken care of, let’s move on to the fizzy stuff!
 
Statistics: A Two-Drink Minimum Science
Although
heavily grounded in mathematics, statistics is...well...weird!
Seriously - if you ever have to start dealing heavily in two-sided
confidence intervals and Student’s T-tests and chi-squared tests (or
anything else squared, for that matter), it can get a little hard to
digest at times.
The Secret Badge of Statisticians Everywhere
You
see, people like me really prefer physical metaphors. I’ve always
liked physics and mechanics, because a lot of the time you can give
yourself a reality check simply by analyzing reality. When you’re
calculating the rate and direction at which an apple falls from a tree,
you can reality check it in your head if your result says the apple
should shoot off straight upward at 1,224 MPH.
At
its best, statistics is understandable and rational; at its worst, it’s
a little strange. Hence, I recommend libations and togas for any
involved statistics discussion. I have asked the fine editors at
Gamasutra to provide such togas and an open digital bar. What, didn’t
you get your passcode? Hmmm, weird.
In any case,
the topics in this article aren’t weird at all. For the most part,
they are tangible, crunchy bits of statistics that you can develop gut
feels for.
Statistics: The Dark Science
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A Statistician Hard at Work
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Statistics is, of all the sciences, the one that is very prone to
misuse by the Forces of Evil. That is, if you had to attribute one
science to the villain you are creating for your new book (you are
writing a book, aren’t you?), you could do much worse than pick
statistics. You could also give him a cape, dress him in black, and
refer to him as “The Spider” or “Mr. Jones”, but I digress.
The
reason that statistics can be loosely compared to villainy is that,
used improperly, this branch of science can be called upon to infer all
sorts of relationships that aren’t actually meaningful or even true
(see the end of this article for an example of what I mean). When in
the hands of politicians and other ne’er do wells, this can guide big
decisions. Big decisions based upon inaccurate conclusions are never
good.
All this is to say, statistics is incredibly
useful and helpful when used properly. But like any stuperpower, it can
be applied in nefarious ways, or even just plain dumb ways.
Statistics – What’s All The Fuss About?
I was going to crack my knuckles and write a tight summary, but then
noticed that Wikipedia already had something that was darn near
poetry. Here it is:
Statistics is a
mathematical science pertaining to the collection, analysis,
interpretation, and presentation of data. It is applicable to a wide
variety of academic disciplines, from the physical and social sciences
to the humanities; it is also used for making informed decisions in all
areas of business and government. (Courtesy Wikipedia.org)
That’s actually a very moving passage. In particular, the last bit is the tour de force of the paragraph:
...it is also used for making informed decisions...
Of
course, the writer forgot to add “in game design,” but we can forgive
him his condescension towards our burgeoning industry.
Here’s my own try:
Statistics
is a mathematical science that deals with collecting and analyzing data
in order to determine past trends, forecast future results, and gain a
level of confidence about stuff that we want to know more about. (Courtesy Tylerpedia)
And if I were to modify it for Game Design, I would say (and am, in fact, saying):
Statistics
can help you shine a flashlight upon your broken mechanics and
shattered design dreams. It does this by giving you actual hard,
scientific data to support meaningful design decisions.
What Do We Need to Know?
Statistics, like any hard science, is deep and complex. Like the tour
of Probability in Part 1, this article only touches on a few selected
topics that I, in my unlimited hubris, have deemed Important Enough to
Know®. (Yep – unlike the many TMs I throw around, this one is so potent
it’s registered!)
Pop Quiz Again
I’m sad to say that I have resorted to another test. Don’t hate the Quizza, hate the Quiz.

A Taxed Quizzee
Q1a)
Focus testers have just finished playing through a level in your new
snail racing game “S-car GO!” Twenty testers played, and your are
informed that the lap times came back in a range from 1 min 24 seconds
at the low end to 2 min 32 seconds at the high end. You were expecting
an average time of 2 minutes or so. Was the test a success?
   
Q1b)
You collect more data for the same level, do some analysis, and find
that the stats are: mean = 2 min 5 sec, standard deviation = 45 sec.
Should you be satisfied?
Q2) You design a casual
game that will surely soon be the talk of soccer moms everywhere (an
admirable goal). In final QA, you release a beta build and then take
data on a whole bunch of trial sessions. Over 1,000 play sessions are
recorded, with over 100 unique players (some players were allowed to
play repeated sessions). Crunching the data shows a mean score of
52,000 pts with a standard deviation of 500 pts. Is the game tuned up
enough to release?
Q3) You design an RPG, and then
collect data on how fast it takes new players to progress from level 1
to level 5. The data comes in as follows: 4.6 hrs, 3.9 hrs, 5.6 hrs,
0.2 hrs, 5.5 hrs, 4.4 hrs. 4.2 hrs, 5.3 hrs. Should you calculate the
mean and standard deviation?
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