1. When using a Random() function, normally, a seed is also used to
help produce a "more random" number. As seen with Intel chips, even
this does not produce randomness, just a larger pattern over time.
2. The smaller/faster the looping construct you use, or the faster the
instructions are given, the more likely a pattern is to develop.
3. My "grudge" if you will, is not that the dice are "random" but that
the dice tend to have a pattern at certain intervals of the game. My
own experience of late has been literally no doubles during the start or
mid game, then a wallop of doubles during the end game and especially
the bear-off. For example: I just finished playing three 5 pointers
over the last two nights. IN ALL 3 MATCHES, my opponent out-doubled me
3:1 on doubles IN THE BEAROFF. In two of the matches, my opponent
received 3 doubles in a row during the bearoff, on 3 of the games in
each match. Alas... why I rant about the code as opposed to the number
generator itself.
4. Although I cannot conceive that there is less code executing with
less checkers in play, I can perceive that due to the moves being
executed faster (especially with auto bear-off) requests to the number
generator are sent at less time intervals than in the beginning of the
game, thus possibly leading to seeing repeat #'s and/or doubles more
often, as the generator is being hit faster. With only 36 possible
rolls, the faster I can bang at the # generator with source code, the
more likely I am to get a repeat #.
Adding to this, if the # generator itself is not that great, then the
chance increases.
5. Maybe it's just me, but I have yet to see the same # of doubles
occur in the bearoffs when I play in person than when I play on FIBS.
And with those who know how to
use their lipless cups with a "soft" or "hard" roll from the cup, ya'd
think I'd see more doubles, etc. from the in-person folks than on a
machine! <g>
6. Maybe an explanation on how the number generator works would help?
Is it a constantly running generator, that is "peeked" at while it's
"spinning" or does it generate the number on request? There is a big
difference between those two...
Anyways, food for thought...
--
Dave Hart
dh...@niteshift.com
Team Night Shift: http://www.niteshift.com
I'm afraid you don't know much about random number generation. I don't know
what FIBS uses (marvin very sensibly hasn't published it) but the normal
procedure is to start the generator off at a random point (often seeded from
the clock) and then generate other numbers as required. So it doesn't matter
how fast you ask for them.
--
Stephen Turner sr...@cam.ac.uk http://www.statslab.cam.ac.uk/~sret1/
Stochastic Networks Group, Statistical Laboratory,
16 Mill Lane, Cambridge, CB2 1SB, England Tel.: +44 1223 337955
"Collection of rent is subject to Compulsive Competitive Tendering" Cam. City
: I'm afraid you don't know much about random number generation. I don't know
: what FIBS uses (marvin very sensibly hasn't published it) but the normal
: procedure is to start the generator off at a random point (often seeded from
: the clock) and then generate other numbers as required. So it doesn't matter
: how fast you ask for them.
For the volume of random-numbers needed on Fibs, even a straight loop through
the 36 possible rolls would be like random for an individual player (taken
that every roll in every game is generated by the same loop) ;-)
Sake
--
+------------------- There is a purpose to time: --------------------+
| Sake Blok (sa...@euronet.nl) EuroNet Internet BV |
| http://www.euronet.nl/~sake Herengracht 208-214 |
| phone: +31 (0)20 625 6161 1016 BS Amsterdam |
| fax : +31 (0)20 625 7435 The Netherlands |
+---------- It prevents everything from happening at once.-----------+
Possibly, except when greedy or automove is on. Or in the first game after a
crash, I suppose.
Stephen Turner wrote:
[... elision ...]
> I don't know
> what FIBS uses (marvin very sensibly hasn't published it) but the normal
> procedure is to start the generator off at a random point (often seeded from
> the clock) and then generate other numbers as required.
I wonder how sensible it is, given the number of times we've all
been through these lines of discussion. If Andreas published the
random number generator algorithm, there would be two reasonable
outcomes:
1. People who know something about random number generation would
confirm that he is doing (a version of) the right thing, and
hope to cut down on the traffic in these sorts of threads (there
is, unfortunately, no guarantee, but keep reading).
2. People who know something about random number generation would
suggest improvements, which Andreas would be under no obligation
to incorporate into his code, but at least the discussion would
be informed by the facts.
A general statement of the algorithm could then be published in the
FAQ, to which we could gently guide newbies who wanted to know how
it works.
Either of those alternatives seems better to me than this constant
traffic in statistical (and lesser) musings and guesses. I'm not
suggesting that Andreas publish any code -- it's his baby -- but is
the algorithm for the generator too much to ask to put a damper on
these discussions?
I for one am very tired of them. Yes, I know, I can (and usually
do) delete these threads whenever they appear, but wouldn't real
information be a better solution? I don't see any benefit to
keeping the algorithm secret, and a lot of benefit to educating
everyone on how good random number generation works by providing
a solid example of good practice.
I personally believe that Andreas know what he's doing. I wish
everyone else did.
My $.02, obviously; your mileage will certainly vary.
Regards,
Richard (moderately competent in statistics) McIntosh
[stuff about random number generators snipped]
ST> I don't
ST> know what FIBS uses (marvin very sensibly hasn't published it)
If FIBS's random number generator can't be manipulated, then I see no sensible
reason why marvin shouldn't publish this information. It could prevent lots of
articles in this newsgroup about FIBS's /supposed/ method for this from being
written and posted.
Like this one ;)
--
<tsb>Zorba
No it wouldn't. 99% of the population wouldn't understand it anyway,
and they'd still be skeptical. Worse, they'd believe that the 1% who
do understand the algorithm have some method of controlling it.
At pseudo-random intervals, some nutcase would come out of the
woodwork pointing out some allegedly well-known flaw in the algorithm,
like it repeats every 13 billion rolls, and we'd have another round of
skepticism.
We'll always have dice-skepticism, it's just a matter of choosing your
flavor.
-Patti
--
Patti Beadles | Knowing how to play well doesn't
pat...@netcom.com/pat...@gammon.com | win-- you must actually do it.
http://www.gammon.com/ |
or just yell, "Hey, Patti!" | No longer pa...@velo.com
I'm more pessimistic than you. Two reasonable outcomes, but four very
likely unreasonable ones too:
3) The people who post "unfair dice" theories without reading past stuff
still would.
4) People who didn't understand the program or formula wouldn't try to, but
would continue with their conspiracy theories.
5) Other people would spot (false) loopholes in the algorithm, and post
"evidence" that it is non-random in some way.
6) Lots of people would badger marvin with suggestions for supposed
improvement.
When was the last time you heard a competent mathematician or a good player
who thought that FIBS dice were non-random? And how many of the doubters
do you think would be persuaded even if the formula were published?
--
Stephen Turner sr...@cam.ac.uk http://www.statslab.cam.ac.uk/~sret1/
Statistical Laboratory, 16 Mill Lane, Cambridge, CB2 1SB, England
"This store will remain open during modernisation. We apologise
for any inconvenience this may cause" Topshop, Cambridge
PB> Robert-Jan Veldhuizen <veld...@xs4all.nl> wrote:
>>If FIBS's random number generator can't be manipulated, then I see no
>>sensible reason why marvin shouldn't publish this information. It could
>>prevent lots of articles in this newsgroup about FIBS's /supposed/ method
>>for this from being written and posted.
PB> No it wouldn't. 99% of the population wouldn't understand it anyway,
I think you greatly underestimate FIBS's users.
I don't really understand Backgammon, for instance, but I'm still interested in
what, let's say, Kit Woolsey has to say about it. I would believe most of it,
even if I don't (yet) underastand it fully.
PB> and they'd still be skeptical. Worse, they'd believe that the 1% who
PB> do understand the algorithm have some method of controlling it.
Why think so negative about 99% of FIBS's users ?
PB> At pseudo-random intervals, some nutcase would come out of the
PB> woodwork pointing out some allegedly well-known flaw in the algorithm,
PB> like it repeats every 13 billion rolls, and we'd have another round of
PB> skepticism.
Maybe. But at least we would then have some facts to argue with, instead of all
the vague idea's we have to come up with now.
PB> We'll always have dice-skepticism, it's just a matter of choosing your
PB> flavor.
Bringing it out in the open and clear could at least clarify lots of things.
Without any information on FIBS's dice, it's almost *obligatory* to be
skeptical.
--
<tsb>Zorba
[why doesn't marvin tell us something about FIBS RNG]
ST> I'm more pessimistic than you. Two reasonable outcomes, but four very
ST> likely unreasonable ones too:
ST> 3) The people who post "unfair dice" theories without reading past stuff
ST> still would.
That's no argument *against* publishing it.
ST> 4) People who didn't understand the program or formula wouldn't try to,
ST> but
ST> would continue with their conspiracy theories.
Do you mean that keeping something "secret" is the way to fight "conspiracy
theories" ?
ST> 5) Other people would spot (false) loopholes in the algorithm, and post
ST> "evidence" that it is non-random in some way.
If it was true, that would only be good. If it was false, we would now have
arguments with which to convince those persons, instead of (as happens so often
now) saying "You're paranoid" or something.
ST> 6) Lots of people would badger marvin with suggestions for supposed
ST> improvement.
Still better than badging him with questioning the RNG FIBS uses.
ST> When was the last time you heard a competent mathematician or a good
ST> player who thought that FIBS dice were non-random?
Another argument, it seems, to *inform* people instead of keeping things secret.
ST> And how many of the
ST> doubters do you think would be persuaded even if the formula were
ST> published?
We can only know if marvin does exactly that.
--
<tsb>Zorba
> PB> No it wouldn't. 99% of the population wouldn't understand it anyway,
>I think you greatly underestimate FIBS's users.
I think you greatly underestimate the subtleties of random number
generation.
> PB> woodwork pointing out some allegedly well-known flaw in the algorithm,
> PB> like it repeats every 13 billion rolls, and we'd have another round of
> PB> skepticism.
>Maybe. But at least we would then have some facts to argue with, instead of all
>the vague idea's we have to come up with now.
Hey, the tools exist to analyze the dice right now. Check out the
commands "dicetest" and "matrix" for good information about the dice.
There's plenty of information there for analysis, but nobody who
complains ever bothers to look at it... it's far too easy to come up
with vague and unsubstantiated generalizations, and far too much work
to look at the data and find out that you're wrong.
>
> When was the last time you heard a competent mathematician or a good player
> who thought that FIBS dice were non-random?
>
Let me offer my opinion. I am not here to trumpet academic credentials,
but I believe that I do understand probability and statistics enough to
make reasonable statements. I also am a competent (but not expert)
backgammon player (FIBS rating of ~1670).
For the past week or so I have been collecting data to see if FIBS produces
outcomes that are consistent with expected random behavior. Specifically,
I have been observing whether getting men off the bar is more difficult
than one would expect. Every time there were men on the bar I observed how
many possible landing spaces there were (open, blots or held by friendly
troops) and whether or not the roll succeeded in landing at least one man
off the bar. (I did not concern myself with the issue of more than one man
on the bar.)
Probability theory suggests that if there is one landing pace, there will
be a successful roll 11/36 of the time; 2 spaces 20/36; 3 spaces 27/36; 4
spaces 32/36; 5 spaces 35/36. I observed the following data:
landing Total Expected
spaces rolls Successes Failures successes Variance
1 104 21 85 32.39 22.49
2 97 46 51 53.89 23.95
3 108 83 25 81 20.25
4 63 53 10 56 6.22
5 57 56 1 55.42 1.54
As you can see from the data there were fewer successes than expected for
the instances when there were 1, 2 and 4 landing spaces, and basically
matching the expectation if there were 3 or 5 landing spaces. The question
then is whether the difference between the observation and the expectation
is statistically significant.
I will aggregate the data together: total number of successes was 259, the
expected value was 278.69. The variance of this number (the sum of the
variances of each case) is 74.45. By probability theory and by the central
limit theorem, we would expect the statistic
(T-E[T])
-------------
(Var(T))^0.5
to have an approximately normal distribution of mean 0 and variance 1. The
value of this statistic is -2.28. Looking up in a standard normal
probability table there is a probability of 1.1% that this statistic will
have a value of -2.28 or smaller if the probability distribution is
correct. The difference between observation and theory is therefore
statistically significant at the 0.011 level.
There are (at least) three possible hypotheses that can explain this result:
A) FIBS dice are non-random.
B) I happened to observe a non-typical series of rolls, and additional
data will cause the observed data to lose their statistical significance.
C) I was not diligent in my observations, and I incorrectly recorded
actual behavior.
I do not entirely discount hypothesis (C), but I was trying to be fair and
complete in my collection of data. (I was also trying to win the games, so
I may have gotten caught up in the heat of battle.) I did my best.
Hypothesis (B) is also plausible, and additional data will clarify.
But the hypothesis that I believe is (A). I think that FIBS dice are
non-random in the instance of bringing men off the bar.
I would be happy to see someone write an observation bot that observes
games and records similar data. I know programmers are not uncommon in the
usenet community, I offer this as a challenge. A bot would be able to
record a greater number of data and not be as subject to the criticism that
data were recorded incorrectly. This would go futther to discount
hypotheses (B) and (C) than I can do by hand.
In any event, it seems to me not impossible that FIBS, for whatever reason,
may have dice that are non-random for some situations. I would be happy if
someone could correct me, but that is what my data say to me.
Respectfully submitted,
Rob Smith
>
> I think that FIBS dice are
> non-random in the instance of bringing men off the bar.
>
> Respectfully submitted,
>
> Rob Smith
If anyone is having trouble replying to my posted e-mail address please
reply to me at robs...@u.washington.edu. The address in the header is
supposed to work, but seems not to be working correctly today.
Rob
snip...
>In article <333280...@cam.ac.uk>, Stephen Turner <sr...@cam.ac.uk> wrote:
>For the past week or so I have been collecting data to see if FIBS produces
>outcomes that are consistent with expected random behavior. Specifically,
>I have been observing whether getting men off the bar is more difficult
>than one would expect. Every time there were men on the bar I observed how
>many possible landing spaces there were (open, blots or held by friendly
>troops) and whether or not the roll succeeded in landing at least one man
>off the bar. (I did not concern myself with the issue of more than one man
>on the bar.)
snip...
>I observed the following data:
>landing Total Expected
>spaces rolls Successes Failures successes Variance
> 1 104 21 85 32.39 22.49
> 2 97 46 51 53.89 23.95
> 3 108 83 25 81 20.25
> 4 63 53 10 56 6.22
> 5 57 56 1 55.42 1.54
NOTE: case 1 has an addition error (104 does not equal 21+85). Assume
21, 85 correct, and roll count is 106. This fits the "expected
successes"
I will requote the raw data with altered statistical analysis:
landing Total Expected std. dev in
spaces rolls Successes successes expectation "zeta"
1 106 21 32.39 4.123 -2.76
2 97 46 53.89 4.943 -1.60
3 108 83 81 4.404 +0.45
4 63 53 56 2.900 -1.03
5 57 56 55.42 1.000 +0.58
This is an interesting result, with a zeta of -2.76 in one case. But
as an isolated experiment, it is inconclusive.
>As you can see from the data there were fewer successes than expected for
>the instances when there were 1, 2 and 4 landing spaces, and basically
>matching the expectation if there were 3 or 5 landing spaces. The question
>then is whether the difference between the observation and the expectation
>is statistically significant.
>I will aggregate the data together: total number of successes was 259, the
>expected value was 278.69. The variance of this number (the sum of the
>variances of each case) is 74.45. By probability theory and by the central
>limit theorem, we would expect the statistic
> (T-E[T])
>-------------
>(Var(T))^0.5
>to have an approximately normal distribution of mean 0 and variance 1. The
>value of this statistic is -2.28. Looking up in a standard normal
>probability table there is a probability of 1.1% that this statistic will
>have a value of -2.28 or smaller if the probability distribution is
>correct. The difference between observation and theory is therefore
>statistically significant at the 0.011 level.
Again suggestive, but not conclusive in isolation.
>There are (at least) three possible hypotheses that can explain this result:
>A) FIBS dice are non-random.
>B) I happened to observe a non-typical series of rolls, and additional
>data will cause the observed data to lose their statistical significance.
>C) I was not diligent in my observations, and I incorrectly recorded
>actual behavior.
>I do not entirely discount hypothesis (C), but I was trying to be fair and
>complete in my collection of data. (I was also trying to win the games, so
>I may have gotten caught up in the heat of battle.) I did my best.
>Hypothesis (B) is also plausible, and additional data will clarify.
>But the hypothesis that I believe is (A). I think that FIBS dice are
>non-random in the instance of bringing men off the bar.
Without offense to you, I will not trust manual counting except when
the counter is not distracted. I think (C) has a high likelyhood, due
to human nature... it is difficult to _reliably_ gather data when even
mildly distracted.
>I would be happy to see someone write an observation bot that observes
>games and records similar data.
This is an excellent proposal.
Greycat
Gre...@tribeca.ios.com
Does anyone have any spare tunafish??
In article <smith-ya02408000...@news.u.washington.edu>,
sm...@ieng.washington.edu (Robert P. Smith) wrote:
> In article <333280...@cam.ac.uk>, Stephen Turner <sr...@cam.ac.uk> wrote:
>
> >
> > When was the last time you heard a competent mathematician or a good player
> > who thought that FIBS dice were non-random?
> >
>
> Let me offer my opinion. I am not here to trumpet academic credentials,
> but I believe that I do understand probability and statistics enough to
> make reasonable statements. I also am a competent (but not expert)
> backgammon player (FIBS rating of ~1670).
>
> For the past week or so I have been collecting data to see if FIBS produces
> outcomes that are consistent with expected random behavior. Specifically,
> I have been observing whether getting men off the bar is more difficult
> than one would expect. Every time there were men on the bar I observed how
> many possible landing spaces there were (open, blots or held by friendly
> troops) and whether or not the roll succeeded in landing at least one man
> off the bar. (I did not concern myself with the issue of more than one man
> on the bar.)
>
> Probability theory suggests that if there is one landing pace, there will
> be a successful roll 11/36 of the time; 2 spaces 20/36; 3 spaces 27/36; 4
> spaces 32/36; 5 spaces 35/36. I observed the following data:
>
> landing Total Expected
> spaces rolls Successes Failures successes Variance
> 1 104 21 85 32.39 22.49
> 2 97 46 51 53.89 23.95
> 3 108 83 25 81 20.25
> 4 63 53 10 56 6.22
> 5 57 56 1 55.42 1.54
>
> As you can see from the data there were fewer successes than expected for
> the instances when there were 1, 2 and 4 landing spaces, and basically
> matching the expectation if there were 3 or 5 landing spaces. The question
> then is whether the difference between the observation and the expectation
> is statistically significant.
>
> I will aggregate the data together: total number of successes was 259, the
> expected value was 278.69. The variance of this number (the sum of the
> variances of each case) is 74.45. By probability theory and by the central
> limit theorem, we would expect the statistic
>
> (T-E[T])
> -------------
> (Var(T))^0.5
>
> to have an approximately normal distribution of mean 0 and variance 1. The
> value of this statistic is -2.28. Looking up in a standard normal
> probability table there is a probability of 1.1% that this statistic will
> have a value of -2.28 or smaller if the probability distribution is
> correct. The difference between observation and theory is therefore
> statistically significant at the 0.011 level.
>
> There are (at least) three possible hypotheses that can explain this result:
>
> A) FIBS dice are non-random.
> B) I happened to observe a non-typical series of rolls, and additional
> data will cause the observed data to lose their statistical significance.
> C) I was not diligent in my observations, and I incorrectly recorded
> actual behavior.
>
> I do not entirely discount hypothesis (C), but I was trying to be fair and
> complete in my collection of data. (I was also trying to win the games, so
> I may have gotten caught up in the heat of battle.) I did my best.
>
> Hypothesis (B) is also plausible, and additional data will clarify.
>
> But the hypothesis that I believe is (A). I think that FIBS dice are
> non-random in the instance of bringing men off the bar.
>
> I would be happy to see someone write an observation bot that observes
<A lot of math which demonstrates that, given the assumption that the
dice are random, the probability of being as far from the norm as the
collected data is is about 1.1%. I don't claim to follow the math, but I
will assume for the sake of argument that it is correct.>
: There are (at least) three possible hypotheses that can explain this result:
: A) FIBS dice are non-random.
: B) I happened to observe a non-typical series of rolls, and additional
: data will cause the observed data to lose their statistical significance.
: C) I was not diligent in my observations, and I incorrectly recorded
: actual behavior.
: I do not entirely discount hypothesis (C), but I was trying to be fair and
: complete in my collection of data. (I was also trying to win the games, so
: I may have gotten caught up in the heat of battle.) I did my best.
: Hypothesis (B) is also plausible, and additional data will clarify.
: But the hypothesis that I believe is (A). I think that FIBS dice are
: non-random in the instance of bringing men off the bar.
Hmmm. So it appears we have to choose between the following hypotheses:
1) The data collection wasn't accurate, which certainly seems possible
given the way the data was collected.
2) Old lady luck, which will cause this offbeat result a little over 1%
of the time.
3) Marvin, that evil man, intentionally subverts his own product, for no
apparent reason whatsoever. Considering that Marvin wrote FIBS not for
profit but for his own ego satisfaction and to supply a working
backgammon server for the internet, I guess we can estimate this
probability at .0001%.
4) The random number generator has suddenly taken a life of its own,
learned to examine backgammon positions, and spit out extra flunking
numbers when a player is on the bar. Tough to judge -- I'd put that
probability at, say, .000001%.
So, now we have to make a value judgment on what the real cause is. My
money is on 1) or 2). Anybody else?
: I would be happy to see someone write an observation bot that observes
: games and records similar data. I know programmers are not uncommon in the
: usenet community, I offer this as a challenge. A bot would be able to
: record a greater number of data and not be as subject to the criticism that
: data were recorded incorrectly. This would go futther to discount
: hypotheses (B) and (C) than I can do by hand.
Guess what -- it's already been done. A couple of years ago Mark Damish
wrote his Big_Brother program which does exactly that -- automatically
observes and records backgammon matches played on FIBS. These matches
are stored on Patti's ftp site, I believe. So, all you have to do is dig
them up, play through a bunch of them, and record the results when a
player is on the bar. Not a difficult project. And since most of the
matches are between high-rated players it could be instructive as well.
Btw, my money says that when you have done this for, say, 5000 samples,
the results will be within two standard deviations of the norm. Anybody
willing to bet otherwise?
Kit
>You can't possibly expect anyone to take seriously any conclusions you
>choose to draw from your tiny sample of 429 rolls ... but your idea for
>program to observe and record such off-the-bar rolls seems like a good
>way to collect a meaningfully larger sample.
I'm far from a stastician, but I seem to remember that a sample size of
greater than 400 is plenty big to draw conclusions from. National poll
sample sizes range from 400-3000 I believe. Course I could be wrong.
Chris
--
------------------------------------------------------------------------
| Chris Wilson "Give me old Buffett music or give me the BeeGees" |
|------------------------------------------------------------------------|
| http://www.iei.net/~wilson/work/biz.html for web design |
| http://www.iei.net/~wilson/boots.html for trading |
|------------------------------------------------------------------------|
| If you're bored enough to read this, you're bored enough to visit my |
| home page at <http://www.iei.net/~wilson> |
------------------------------------------------------------------------
You can't possibly expect anyone to take seriously any conclusions you
choose to draw from your tiny sample of 429 rolls ... but your idea for
program to observe and record such off-the-bar rolls seems like a good
way to collect a meaningfully larger sample.
[nothing but smith follows ...]
>There are (at least) three possible hypotheses that can explain this result:
>A) FIBS dice are non-random.
>B) I happened to observe a non-typical series of rolls, and additional
>data will cause the observed data to lose their statistical significance.
>C) I was not diligent in my observations, and I incorrectly recorded
>actual behavior.
>I do not entirely discount hypothesis (C), but I was trying to be fair and
>complete in my collection of data. (I was also trying to win the games, so
>I may have gotten caught up in the heat of battle.) I did my best.
>Hypothesis (B) is also plausible, and additional data will clarify.
>But the hypothesis that I believe is (A). I think that FIBS dice are
>non-random in the instance of bringing men off the bar.
>I would be happy to see someone write an observation bot that observes
>games and records similar data. I know programmers are not uncommon in the
>usenet community, I offer this as a challenge. A bot would be able to
>record a greater number of data and not be as subject to the criticism that
>data were recorded incorrectly. This would go futther to discount
>hypotheses (B) and (C) than I can do by hand.
>In any event, it seems to me not impossible that FIBS, for whatever reason,
>may have dice that are non-random for some situations. I would be happy if
>someone could correct me, but that is what my data say to me.
>Respectfully submitted,
>Rob Smith
--
_______________________________________________________
Daniel Murphy | San Francisco | rac...@cityraccoon.com
Monthly tourneys in San Mateo: See www.gammon.com/bgbb/ for details
and some excellently annotated matches. On-line: telnet fibs.com 4321.
First, let me commend you on actually producing actual numbers rather
than just random unsubstantiated rantings. This is a far cry better
than the usual FIBS dice debates.
There is a large database of saved matches on http://www.gammon.com/
... look for the Big Brother matches. It should be a relatively
simple programming exercise to walk through all of the games, find
positions where someone is entering from the bar, count the valid
rolls, and keep track of whether or not he entered.
I suspect that B and C are about equally correct.
-Patti
--
Patti Beadles |
pat...@netcom.com/pat...@gammon.com |
http://www.gammon.com/ | "I trust you. It's just
or just yell, "Hey, Patti!" | that I'm scared of you."
wil...@iei.net (Chris Wilson) writes:
>In article <raccoon.859459803@shellx>, rac...@best.com (Daniel Murphy) wrote:
>>You can't possibly expect anyone to take seriously any conclusions you
>>choose to draw from your tiny sample of 429 rolls ... but your idea for
>>program to observe and record such off-the-bar rolls seems like a good
>>way to collect a meaningfully larger sample.
>I'm far from a stastician, but I seem to remember that a sample size of
>greater than 400 is plenty big to draw conclusions from. National poll
>sample sizes range from 400-3000 I believe. Course I could be wrong.
Chris, we're not talking here about opinion polls or the accuracy of
surveys using representative sampling. We're talking about a random
number generator which simulates rolling two dice and the 36 possible ways
they can be thrown. The statistics provided were further subdivided into
6 different categories, depending on how many home board points were open
when the dice were rolled -- so the samples provided were actually much
smaller than 429 -- approximately 50 to 100 instances of each case.
Rolling dice 50 times and noting how often a 1 in 36 possibility occurs,
or rolling dice 100 times and seeing how often a 1 in 3 or 20 in 36
possibility occurs proves nothing -- unless the results are so far off as
to make it impossible for the dice to be fair, which wasn't the case with
the statistics provided.
So yes, the sampling provided was so small that it would be absurd to
think it proves anything at all about the random number generator.
Maybe I've missed something, but I've never seen any "claim" from anyone from
FIBS stating that the dice are random. Nothing on FIBS, nothing in the FAQ or
elsewhere on the WWW, nor anything in this newsgroup.
I would trust any statement, I even asked for it once, but didn't get any
reply...
I wonder what most BGplayers would prefer when playing in a club against someone
they don't know: 1. The opponent just calls his rolls, saying for example "five
six", without any way to check if he really rolls (fairly) random dice, or 2.
The opponent shows you his dice and how he rolls them.
Well good luck to all anyway :)
Cheers,
--
<tsb>Zorba
>> PB> No it wouldn't. 99% of the population wouldn't understand it anyway,
>>I think you greatly underestimate FIBS's users.
PB> I think you greatly underestimate the subtleties of random number
PB> generation.
Thank you for proving my point and putting me in that 99% of yours...
>> PB> woodwork pointing out some allegedly well-known flaw in the algorithm,
>> PB> like it repeats every 13 billion rolls, and we'd have another round of
>> PB> skepticism.
>>Maybe. But at least we would then have some facts to argue with, instead of
>>all the vague idea's we have to come up with now.
PB> Hey, the tools exist to analyze the dice right now. Check out the
PB> commands "dicetest" and "matrix" for good information about the dice.
Done that, nothing about the RNG FIBS uses.
PB> There's plenty of information there for analysis, but nobody who
PB> complains ever bothers to look at it... it's far too easy to come up
PB> with vague and unsubstantiated generalizations, and far too much work
PB> to look at the data and find out that you're wrong.
*sigh* Let me refresh your memory: I analyzed 5 million rolls and the amount of
doubles FIBS throwed was far too high; chances of that many doubles or more
occuring are less than 0.1%. Posted not too long ago in rgb. Confirmed by
Stephen Turner and mailed to you and marvin.
I never got any reply on that...so, I don't know what you mean with your remarks
above.
Cheers,
--
<tsb>Zorba
This (LONG) post has three parts: A) soapbox (mild scolding of some
r.g.b. posters), B) rework of Rob Smith's original analysis, and
C) analogy to modern scientific practice and proposal for further study.
A) SOAPBOX stuff (IHMO, as always):
I find Rob's post sincere, diligent, and interesting. Here is an
attempt to question the randomness of FIBS dice, and it's done with
intelligence, rigor, and (apparently) without emotional involvement.
This is what randomness "believers" have been crying for forever.
I think it should be addressed with AT LEAST as much sincerity,
diligence, and emotionlessness. Anything less places posters back
in the stone age (REGARDLESS of which side of the debate you are on).
I have a lot of respect for the posters whose replies I have read.
However, there are three arguments in particular that I've seen, and don't
like. Paraphrased: 1) "this proposal is so preposterous and FIBS so
beyond reproach that it isn't worth considering". With this general
attitude, we'd ALL still be in the above mentioned stoneage. 2) "You
can't believe any result which is based on small number of trials."
I believe this statement shows a lack of understanding of statistics.
More will be said about this in part C below, but consider the following:
Suppose Rob's study showed 5 entries total (say, one for each of the five
inner board conditions) out of the same 431 trials. Would you still say
that 431 wasn't a large enough sample? I would certainly ask for further
study (as I am doing here) but not because the sample size was too small!
3) "This study is meaningless." Maybe just a poor choice of words, but not
at all an objective, scientific statement!
I am NOT an expert on statistics. You don't need to be to apply
them (intelligently) to backgammon. I've only taken one elementary prob.
and stat. class in my life. I have learned some by reading, thinking, and
discussing with those more versed in the subject than I. Thus I certainly
could be way off in what I have to say. Frankly, I'd like to see posts
from experts in the field. I believe that Fredrik Dahl, Bob Koca, and
Steven Turner may be experts. (How could anyone with "University of
Cambridge Statistics Laboratory" in his mail headers/trailers NOT be able
to do this stuff with his left hand tied behind his back!)
B) REWORK of Rob Smith's original analysis:
In article <smith-ya02408000...@news.u.washington.edu>,
Robert P. Smith <sm...@ieng.washington.edu> wrote:
(snip)
>For the past week or so I have been collecting data to see if FIBS produces
>outcomes that are consistent with expected random behavior. Specifically,
>I have been observing whether getting men off the bar is more difficult
>than one would expect. Every time there were men on the bar I observed how
>many possible landing spaces there were (open, blots or held by friendly
>troops) and whether or not the roll succeeded in landing at least one man
>off the bar. (I did not concern myself with the issue of more than one man
>on the bar.)
I'm a bit confused here. Did you or did you not include the "more
than one checker on the bar" case in your study??
CRB
>
>Probability theory suggests that if there is one landing pace, there will
>be a successful roll 11/36 of the time; 2 spaces 20/36; 3 spaces 27/36; 4
>spaces 32/36; 5 spaces 35/36. I observed the following data:
>
>landing Total Expected
>spaces rolls Successes Failures successes Variance
> 1 106* 21 85 32.39 22.49
> 2 97 46 51 53.89 23.95
> 3 108 83 25 81 20.25
> 4 63 53 10 56 6.22
> 5 57 56 1 55.42 1.54
>
totals 431 259 172 278.69 74.45 (line by CRB)
* corrected from "104" of original post.
>
>As you can see from the data there were fewer successes than expected for
>the instances when there were 1, 2 and 4 landing spaces, and basically
>matching the expectation if there were 3 or 5 landing spaces. The question
>then is whether the difference between the observation and the expectation
>is statistically significant.
>
>I will aggregate the data together: total number of successes was 259, the
>expected value was 278.69. The variance of this number (the sum of the
>variances of each case) is 74.45. By probability theory and by the central
>limit theorem, we would expect the statistic
>
> (T-E[T])
>-------------
>(Var(T))^0.5
>
>to have an approximately normal distribution of mean 0 and variance 1. The
>value of this statistic is -2.28. Looking up in a standard normal
>probability table there is a probability of 1.1% that this statistic will
>have a value of -2.28 or smaller if the probability distribution is
>correct. The difference between observation and theory is therefore
>statistically significant at the 0.011 level.
>
>There are (at least) three possible hypotheses that can explain this result:
>
>A) FIBS dice are non-random.
>B) I happened to observe a non-typical series of rolls, and additional
> data will cause the observed data to lose their statistical significance.
>C) I was not diligent in my observations, and I incorrectly recorded
> actual behavior.
I have two technical concerns about this analysis. Again--disclaimer
--I could be wrong on both (and thus Rob right on both). Let's hear from
you other pencil pushers!
1) If Rob would have also made a similar post if the number of entries
had been TOO LARGE by 2.28 standard deviations, then you must multiply
the 1.1% by 2. The jargon used here is "two-tailed" versus "one-tailed"
analysis. The Gaussian (normal, bell-shaped, etc.) distribution mentioned
by Rob above is symmetric. He took only the area under to LOW SIDE tail
to come up with his number. (That is, there is a 1.1% chance of getting
too few entries by this amount.) BUT, the HIGH SIDE tail represents the
chance of getting too many entries. Thus if this would garner equal
eyebrow raising, it is only fair to say "the chances of the number of
entries being off by 2.28 standard deviations or more is 2.2%").
2) I see another way to analyze the data. (NOTE: SINCE MY ANSWER
DISAGREES WITH ROB, AT MOST ONE OF US IS DOING IT CORRECTLY! I challenge
all of you to find out which one (IF EITHER) is doing the analysis right.)
The sum of the expected outcomes is 278.69 Entries (and 152.31 Wiffs).
So the standard deviation (for a binomial distribution) for 431 trials is:
srqt( e*w/n ) = sqrt( 278.69 * 152.31 / 431) = 9.92
(NOTE that Rob's method gets sqrt(74.45) = 8.63 for the standard dev.)
Now, dividing this into the difference (278.69 - 259)/9.92 = 1.98
standard deviation result (instead of the 2.28 s.d. result Rob indicates).
Although this doesn't seem like much of a difference, in fact it results
in another factor of two (because the Gaussian distribution is non-linear).
In summary of part 2, my conclusion is that Rob's data indicates
a 4.7% chance that the hypothesis "FIBS gives randomly distributed dice
rolls when entering a single checker from the bar" is correct. (BTW, my
indiscriminate rework of the data in part A to 5 entries in 431 trials
would be a whopping 27.6 std.dev. result. This is 1 chance in 10^166 !!
That's a pretty small likelihood...)
C) analogy to modern scientific practice and proposal for further study.
I am now going to relate how this kind of issue is handled in
the scientific literature (specifically in physics and astronomy,
and I assume also in geology, chemistry, biology, and mathematics).
Qualitatively, the following quote from Carl Sagan (from the
book "UFO's: A Scientific Debate" Sagan and Page (eds.) W.W. Norton
1972, p. 265) describes the general approach taken in real science:
There is a wide range of concepts which would be fascinating
if only they were true. But precisely because these ideas
have charm, exactly because they are of deep emotional
significance to us, they are the ideas we must examine most
critically. We must consider them with the greatest
skepticism, and exmaine in the greatest detail the evidence
relevant to them. Where we have an emotional stake in an
idea, we are most likely to deceive ourselves.
Although he was referring to issues of far greater importance than
what has been presented on this newsgroup, these principles apply.
The procedure in science would be for the author(s), in this
case Rob, to submit a manuscript to the editor of a journal. If
a refereed journal, the editor would pass a few copies on to persons
who are widely recognized to be knowledgeable on the particular
subject (random numbers and generators). These referees would read
the paper and submit questions and suggestions to the author through
the editor. They would also make a judgement as to whether the
information reported is appropriate for publication in this journal.
The referee's reports would then be given back to the author for
rebuttal. If the objections weren't severe, usually the author will
either modify the paper to address the questions/suggestions of the
referees, or write replies addressing those concerns and explain why
the paper was not modified. The editor will then decide whether to
pass this new work on to the referees for further recommendations or
just go ahead with publication. Some papers will be rejected without
further review (with a suggestion for major rewrite and resubmission)
but typically papers are accepted for publication (in experience and
fields, anyway). NOTE: The referees are NOT being asked to agree or
disagree with the result, but only to judge the legitimacy of the
techniques (data taking and analysis). To do more would be a
disservice to the progress of knowledge.
Publication in no way guarantees acceptance of the ideas!
The (critical) scientific readership is basically the jury. If they
disagree, typically some will propose new experiments (and acquire
funding and perform those experiments). These new studies will either
confirm or refute the original ideas (or possibly be inconclusive).
Subsequent papers will be submitted and published and the cycle
continues. It may take many years for ideas to be accepted, particularly
new, revolutionary concepts. There is never 100% guaranteed "fact".
Classical mechanics ideas (of Galileo, Decartes, Newton, etc.) stood
as the "last word" for 200 years until modified in the early part of
this century by many including Bohr, Born, Einstein, Shroedinger, etc.
Someday their ideas are likely to be overthrown (or at least updated).
Often in parallel to the experimental reporting of observations,
theorists will try to explain how these results come about. There is
a back and forth exchange of ideas MOST OF WHICH TURN OUT TO BE WRONG!
These are the inevitable growing pains of scientific ideas. Much of
what you read in newspapers about "black and white" or "right and wrong"
or "fact and fantasy", when given in absolute terms, is not real
science, no matter how convincing the arguments seem to be. It sells
papers, but it's not proper science. The apostle, Thomas, was surely
a scientist! And it's no surprise that very few politicians
have a clue of how science is done. Authoritarianism and deal making
are unfortunately present in science as well, but to the detriment of
true knowledge. Skepticism is healthy, and a fundamental requirement
for progress in science.
Now, back to this standard deviation, confidence level stuff.
There is no clear cut criterion (that I know of, anyway) for converting
statistical confidence to acceptance of an idea. For example, if a school
student comes to you and says that s/he has done a statistical survey
and concluded wtih 95% confidence (2-tailed 2 standard deviation result)
that there are fewer left handed people than right handed, you'd probably
yawn and go back to reading your paper. Since this is status quo
(the "accepted" truth) there is no reason to get excited. If the next
day that same student reports to you that another study produced a 95%
statistical confidence result that left handers are smarter than right
handers, you might raise your eyebrows and start asking some questions
(unless you happened to be one of these intellectually superior south-
paws)! And if later s/he announces that there is 95% confidence result
that left handers were deposited here on the earth by UFO's, even the
most laid-back sinesterian would likely snap to attention! "...(for)
concepts which would be fascinating, ...we must consider them with the
greatest skepticism, and examine in the greatest detail the evidence
relevant to them."
So this 2.28 (1.98) single-tailed (two-tailed) result reported
by Rob should pique our interests. Either it will be refuted by further
testing (supporting the status quo), in which case FIBS will be safe for
all of humanity, or it will be confirmed (at a much higher confidence
level!) and we will re-evaluate the worth of time spent playing on the
server. It is this higher confidence level search which necessitates
more data taking NOT the mere requirement of larger sample size. If
431,000 trials results in a two standard deviation discrepancy, we won't
be any farther along than we are now. So do your stuff, computer jockeys.
I'm waiting impatiently (but emotionlessly).
Chuck
bo...@bigbang.astro.indiana.edu
c_ray on FIBS
Much snippage follows, I do not attempt to mark it all.
There is an allegation that bo...@bigbang.astro.indiana.edu (Chuck
Bower) wrote:
> This (LONG) post has three parts: A) soapbox (mild scolding of some
>r.g.b. posters), B) rework of Rob Smith's original analysis, and
>C) analogy to modern scientific practice and proposal for further study.
>A) SOAPBOX stuff (IHMO, as always):
> I find Rob's post sincere, diligent, and interesting. Here is an
>attempt to question the randomness of FIBS dice, and it's done with
>intelligence, rigor, and (apparently) without emotional involvement.
>This is what randomness "believers" have been crying for forever.
> I think it should be addressed with AT LEAST as much sincerity,
>diligence, and emotionlessness. Anything less places posters back
>in the stone age (REGARDLESS of which side of the debate you are on).
I agree. His method is unreliable, but at least he _attempts_ to get
real results. For that, I give him much credit for.
>3) "This study is meaningless." Maybe just a poor choice of words, but not
>at all an objective, scientific statement!
Except when a reason is given (and preferably a politely worded way of
saying "meaningless").
>B) REWORK of Rob Smith's original analysis:
> I have two technical concerns about this analysis. Again--disclaimer
>--I could be wrong on both (and thus Rob right on both). Let's hear from
>you other pencil pushers!
>1) If Rob would have also made a similar post if the number of entries
>had been TOO LARGE by 2.28 standard deviations, then you must multiply
>the 1.1% by 2.
Well, this is true, but his error only magnifies the "unusual" result.
My main issues are
Would a "average" result be as likely to be reported? The _media_
is suspect, even if the individual data set is not.
He admits to counting on the fly, while (quickly) playing games.
This creates a very high probability of a counting error, and it
is reasonable to wonder if that error might not be systematic.
(For the non-statistically trained, a systematic error is one that
tends to go in the same direction, rather than to average out).
>C) analogy to modern scientific practice and proposal for further study.
> The procedure in science would be for the author(s), in this
>case Rob, to submit a manuscript to the editor of a journal.
In a sense, he did... this is as much of a journal that exists on the
topic of FIBS. Of course, we don't have an editor (much less a
referee).
Good point. His thesis is hard to believe ... that the rolls are
affected by the precence of men on the bar and of possible entry
rolls. Thus, a very high confidence is needed to accept the theory.
The statistically unusual result reported _does_ justify further
research. But I _strongly_ recommend that the testing be automated,
for reliability. If I didn't have too many programming jobs
backlogged already, I'd take a crack at it. Any one else interested?
I very much appreciate this and other thoughful replies to my original post.
In article <5hjjd8$2...@dismay.ucs.indiana.edu>,
bo...@bigbang.astro.indiana.edu (Chuck Bower) wrote:
> This (LONG) post has three parts: A) soapbox (mild scolding of some
> r.g.b. posters), B) rework of Rob Smith's original analysis, and
> C) analogy to modern scientific practice and proposal for further study.
>
(snip)
>
> B) REWORK of Rob Smith's original analysis:
>
> In article <smith-ya02408000...@news.u.washington.edu>,
> Robert P. Smith <sm...@ieng.washington.edu> wrote:
>
> (snip)
>
> >For the past week or so I have been collecting data to see if FIBS produces
> >outcomes that are consistent with expected random behavior. Specifically,
> >I have been observing whether getting men off the bar is more difficult
> >than one would expect. Every time there were men on the bar I observed how
> >many possible landing spaces there were (open, blots or held by friendly
> >troops) and whether or not the roll succeeded in landing at least one man
> >off the bar. (I did not concern myself with the issue of more than one man
> >on the bar.)
>
> I'm a bit confused here. Did you or did you not include the "more
> than one checker on the bar" case in your study??
> CRB
I treated cases where there were one or more than one man on the bar
equivalently. Did each roll succeed in getting (at least) one man off the
bar?
Two mechanical points:
1) Deciding to use a one-tailed test or a two-tailed test is a
philoposphical difference to which there is not a clean answer. The
outcome of this argument will chance the specific level of significance
produced, but will not materially change the nature of the argument.
2) Treating the total number of successes and failures as a Binomial random
variable in order to calcualte the variance is not correct. Doing so means
that each roll has a chance of success of 0.645. In fact some rolls have a
chance of success of 11/36, some rolls have a chance of success of 5/9,
some rolls have a chance of success of 3/4, and so on. Each line of the
table should have a Binomial distribution, and this is how I calculated the
variance of each line. The variance of the total is the sum of the
variance of each line, which leads to the 8.63 standard deviaion, rather
than the 9.92.
I agree that manual collection of data is inherently suspect. I would
greatly appreciate if someone could write a data collection program either
for the Big Brother games or for ongoing games. Don't worry if you do not
feel prepared to do the statistical analysis required, I and others are
more than willing to use the data once they are gathered.
Respectfully,
Rob Smith