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StatisticsYou've collected and summarized a bunch of data here, but it would be much more useful (and straightforward) to run some inferential procedures (Monte Carlo procedures would be particularly easy to implement in this case) to see if these results were compatible with the hypothesis of a fair game. Give it a try!
Actually - using some optimized queries in MySQL against the tables that were created in the analysis allowed to rank score every conceivable lottery number. Optimization was needed to get the run time down from one year to about 36 hours. But, you don't think I'm going to give away MY number and share that -cough- winning -cough- with everybody?
RE: Where's the analysis?
I did do some analysis. Compensating for the four (ouch) different types, I get an overall p-value of 0.792. This means there is absolutely NO statistical significance...
You can test it yourself if you have R:
#Get big.dat at http://www.state.nj.us/lottery/data/big.dat
big=read.table("big.dat",sep="%",fill=T)
big$date=as.Date(apply(big[,1:3],1,paste,collapse="-"))
big$type=ifelse(big$date>"1999-1-13",ifelse(big$date>"2002-3-15",ifelse(big$date>"2005-06-22",4,3),2),1)
big$maxnorm=c(50,50,52,56)[big$type]
big$maxspecial=c(25,35,52,46)[big$type]
maxnorms=table(big$maxnorm)
p=rep(0,56)
for(i in 1:nrow(maxnorms))
p[1:as.numeric(names(maxnorms)[i])]=p[1:as.numeric(names(maxnorms)[i])]+maxnorms[i]*5
maxspecial=table(big$maxspecial)
for(i in 1:nrow(maxspecial))
p[1:as.numeric(names(maxspecial)[i])]=p[1:as.numeric(names(maxspecial)[i])]+maxspecial[i]
p=prop.table(p)
allnum=unlist(big[,5:10])
t=table(allnum)
chisq.test(t,p=p)
plot(t/p)
P
RE: Where's the analysis?
I can't get over the fact that every ball has an equal chance of coming out. Therefore the sequence 1,2,3,4,5,6 is just as likely to come up as any other sequence. But it never does, so that demonstrates how likely you are to choose a winning sequence.
No amount of ex-post pattern analysis can change that.
RE: Where's the analysis?
I may have missed this in your graphs and charts, (my understanding of math is dubious at best) but I was wondering if you noticed what I noticed. In 2001 I noodled around with the numbers for 2 years in an excel sheet to see what numbers came up the most, and after mapping out the numbers by 3 month seasons I saw an ebb and tide pattern to the grouping of numbers.
For example, the first 5 numbers would have low sequences (mostly from 1 to 20) for couple of weeks, then it would crest to high sequences (mostly 21 and up) for a month and a half or so, and it kept repeating this over the previous couple of years. The Megaball did the same thing, but in an reverse pattern, staying mostly low, and cycling up for a couple of weeks.
At that point I was stuck on how to come up with playable numbers within the two different groupings and never went further.
By the way good thread! And did it ever work out for you?
TMX
themysteriousx@sbcglobal.net
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Where's the analysis?
You've collected and summarized a bunch of data here, but it would be much more useful (and straightforward) to run some inferential procedures (Monte Carlo procedures would be particularly easy to implement in this case) to see if these results were compatible with the hypothesis of a fair game. Give it a try!
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