| Its not exactly the same but its pretty close when the chances are so low anyways. Playing 10,000 times in 1 drawing gives you the probability of winning the jackpot: 0.00003422297813=10000/292201338 Playing 10,000 times in 10,000 drawings gives you the probability of winning the jackpot: 0.00003422239258=1-((292201338-1)/292201338)^10000 The difference gets more significant if you play more. For 10 million plays its: .0342 vs .0336 If you play only 100 times the probability of a jackpot is the same to 7 significant digits. -edit I put it on $1M and let it run. I hit the 5 numbers, $1M prize, at some point around $150k spent. |
For an extreme example, consider a lottery with only one number, selected from 1 to 2, costing $1 per ticket, with a $2 jackpot.
Buy 2 tickets at once, you lose $2 on tickets, and you get $2 back. Expected net return, $0 (with probability 100%).
Buy 1 ticket per draw for 2 draws, and you have a 1/4 chance of winning nothing (net -$2), a 1/4 chance of winning both jackpots (net +$2), and a 2/4 chance of winning one and losing one (net $0). Same expected value.
Of course, in a real lottery, usually[0] the expected value is negative. So what's happening is like anti-insurance. In both cases your expected value is negative, but you pay the insurance company money to lower your variance, and you pay the lottery money to raise your variance.
[0] Usually? Well, in theory with a cumulative jackpot the jackpot might get high enough to make the expected value positive... except that usually as the jackpot rises, the number of players rises too, such that you have to take into account the possibility of having the split the jackpot, which of course would cut your take in half, or worse.