For A or indeed C (ASSUMING p CONSTANT!), you have a Binomial distribution. Written as X~Bin(n, p).
Probability of getting more than k successes:
P(X
>= k) = 1 - P(X
<= k) = 1 - SUM[
from i = 0 to k]
((n choose i)*
(p^i)*
(1-p)^
(n-i))
Which looks horrific. For clarity, n choose i is n!
/ (i!
*(n-i)!)
EDIT: It's been a while since I've done stats. Kind of glad no one posted this whilst I was thinking it over...
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1% is the probability in a single crate. So basically when you open a single crate, theres 1/100 probability of getting an unusual. It has nothing to do with the fact that it takes more than 100 crates to get an unusual, since the probabilities don't add up.
If someone got an unusual on their first try, I'm sure they wouldn't whine about it, although 1/1 also =/= 1/100...
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Been looking at (F).
I reckon (and this is going to be messy as fuck, I apologise). I'm also not clear on whether unusuals can have the same name and different effects? Lets assume so.
Lets define some Binomial distributions, since that is what I think they are (and define a few other things while we are at it).
Let h = number of hats. Let I = number of items in TF2 that can be unusual. Let m = number of different effects
So we have the chance of getting an unusual from opening crates: U~Bin(n, p).
Chance of that unusual being a hat: h/I
Chance of it being our fav. hat: 1/h --> chance of it being our fav hat & unusual: 1/h h/I = 1/I.
Chance of it being our fav. unusual hat with our fav. effect: 1/I 1/m = 1/Im
Sooo, I reckon we can now say that the probability that the crate opens and gives our fav. hat, unusual and effect is p/Im. Because p is already a probability so we don't need to take it's reciprocal...
Now we can define a new Binomial, since U was Binomial in the first place. Lets use Z, because you know, why the fuck not? Z~Bin(n, p/Im)
P(Z
>= k ) = 1 - P(Z
<= k) = 1 - SUM
[from i = 0 to k
](n choose i)*(p/Im^i)*(1-p/Im)^(n-i))
EDIT: So if unusuals can only have one effect, the formula becomes:
P(Z
>= k ) = 1 - P(Z
<= k) = 1 - SUM
[from i = 0 to k
](n choose i)*(p/I^i)*(1-p/I)^(n-i))
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Yea, just drop all the m's from it if the number of effects is the same as the number of different types of unusual (see the edit).
Other than that? No there is no way of simplfying it, not without looking up specific numbers, and I just couldn't be arsed enough to go and find how many hats / effects / items-that-can-be-unusual there are in TF2.
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You could take the limit p gets close to 0 so almost never get unusuals and then the last two terms cancel leaving:
P(Z
>= k ) = 1 - P(Z
<= k) = 1 - SUM
[from i = 0 to k
](n choose i)
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I thought TF2 math was something like "I had 5 hats and gave 2 to a friend, how many hats do I have now?"
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Didn't do anything like that since... 4+ years ago I guess? ;_;
The only thing I know is, I know a guy who had opened 600+ crates and got shit, and I know a guy who got 2 unusuals in 9 crates.
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I myself got a 9 buds unusual out of 3 crates. Sold that unboxed +150 more crates, got shit.
Basically 2.9% chance succeeded and more than 78% chance failed. Also 600 crates gives 99.75% chance of getting at least one unusual! Interesting...
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A) We assume each crate has 1% probability of giving an unusual upon opening. What is the probability of getting at least "k" unusual out of "n" boxes?
B) 3 Refined Metals are needed to craft a random hat. What is the probability of crafting a hat that's worth more than 3 Refined Metals? (Also how many total hats are there and how many of them are worth +4 Refs?)
C) We assume each raffle has "p" probability of winning. What is the probability of winning at least "k" raffles out of "n" raffles. (General form of A)
D) Each Crate #19 is worth 1 Key + 1 Ref and each Strange Grenade Launcher is worth 4 Keys. We assume each crate #19 has 22.5% percent chance of giving a Strange Grenade Launcher upon opening. Each crate #19 opening costs 2 Keys + 1 Ref. How many Crate #19s should we open to have a higher probability of profit than 50%? (Hardcore question)
E) We assume all unusual effects and unusual hats have the same probability of gaining. If "E" is our favorite effect and "H" is our favorite hat. What is the probability of getting a "H" hat with "E" effect if we get an unusual from a crate? (Super Hardcore Question)
F) We assume all unusual effects and unusual hats have the same probability of gaining and each crate has a "p" probability of giving a random unusual upon opening. If "H" is our favorite hat and "E" is our favorite effect. What is the probability of getting at least "k" hats of "H" kind with "E" effect if we open "n" crates? (Mother of all questions)
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