Probability Mass Function of 50 collectibles

In summary, the conversation discusses a problem in which a supermarket gives out a free "collectible" for every 15 Euro's spent, with 50 different types of collectibles available. The goal is to find the probability mass function of the number of additional collectibles needed after collecting a certain number of distinct types, as well as the expectation value of the total number of collectibles needed to obtain a complete set of at least one of each type. The problem is solved using a geometric distribution and the Coupon Collector's Problem is suggested as a helpful resource.
  • #1
Verdict
117
0

Homework Statement


Some supermarket gives its customers a free ”collectible” (C) for every
15 Euro's spent. There are 50 different types of Cs. Assume that each time a
customer receives a C it is equally likely to be one of the 50 types. Define Ni,
i = 1, 2, . . . , 49, to be the number of additional Cs that need to be obtained after
i distinct types have been collected in order to obtain another distinct type, and let
N denote the number of Cs collected to attain a complete set of at least one of
each type.

Find the pmf (probability mass function) of Ni. What famous distribution is this?
(And later, after I figure this one out):
Determine the expectation value of N (so not Ni)

Homework Equations


I can't really think of any at this time, other than maybe pmf (probability mass function) for X is given by fx = P(X=x)

The Attempt at a Solution


Right, so, starting with the pmf of Ni. Ni is the number of collectibles that are still required to be obtained after already getting i of them, so this is 50-i and the pmf has to do with the chance of 'being at a point Ni ', so I'd say that i = 1, or N1 = 49 is the most probably and i = 49 the least.

Now, the (discrete) distributions that I know of are the point mass function, the bernoulli distribution, the binomial distribution, the geometric distribution and the Poisson distribution.
I don't really see which one fits exactly, but a geometric distribution sounds alright. Could anyone provide a hint?
 
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  • #2
Verdict said:

Homework Statement


Some supermarket gives its customers a free ”collectible” (C) for every
15 Euro's spent. There are 50 different types of Cs. Assume that each time a
customer receives a C it is equally likely to be one of the 50 types. Define Ni,
i = 1, 2, . . . , 49, to be the number of additional Cs that need to be obtained after
i distinct types have been collected in order to obtain another distinct type, and let
N denote the number of Cs collected to attain a complete set of at least one of
each type.

Find the pmf (probability mass function) of Ni. What famous distribution is this?
(And later, after I figure this one out):
Determine the expectation value of N (so not Ni)

Homework Equations


I can't really think of any at this time, other than maybe pmf (probability mass function) for X is given by fx = P(X=x)


The Attempt at a Solution


Right, so, starting with the pmf of Ni. Ni is the number of collectibles that are still required to be obtained after already getting i of them. So N49 is where you start at, if I understand correctly.
Now, the pmf has to do with the chance of 'being at a point Ni.' I'd say N49 is the most likely, and N0 the least?

Now, the (discrete) distributions that I know of are the point mass function, the bernoulli distribution, the binomial distribution, the geometric distribution and the Poisson distribution.
None of them really seem to fit the situation in my opinion, so maybe someone could provide a hint as to what to do?

Google "Coupon Collector's Problem".
 
  • #3
So it's a geometric distribution, I already had that feeling. Alright, I'll try and go from there!
 
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  • #4
Ok, so clearly I misread what Ni is. It is the number of C's that have to be collected before having i + 1 different C's.

Would I be correct in thinking that N = 'the sum from i=1 to 49' of Ni, plus 1? (As you have to collect 1 C to get to i = 1)? I googled the problem, but I don't see how this is a geometric distribution. Isn't there supposed to be a constant factor between the terms, like 1/2 + 1/4 + 1/8 etc for it to be a geometric series?

Alright, so again my mistake. A geometric series is not the same category as a geometric distribution. Knowing that, it makes perfect sense. I got it, thanks
 
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  • #5
Verdict said:
Ok, so clearly I misread what Ni is. It is the number of C's that have to be collected before having i + 1 different C's.

Would I be correct in thinking that N = 'the sum from i=1 to 49' of Ni, plus 1? (As you have to collect 1 C to get to i = 1)? I googled the problem, but I don't see how this is a geometric distribution. Isn't there supposed to be a constant factor between the terms, like 1/2 + 1/4 + 1/8 etc for it to be a geometric series?

Alright, so again my mistake. A geometric series is not the same category as a geometric distribution. Knowing that, it makes perfect sense. I got it, thanks

No, no, no. It said very clearly that Ni is the number of *additional* Cs that must be collected to get a new type, after i distinct types have been collected already. So Ni has an ordinary geometric distribution, with 'success' probability dependent on i.

The (random) number of Cs that must be collected altogether until i different types are obtained is the sum ##S_i = 1 + N_1 + N_2 + N_3 + \cdots + N_{i-1}, ## where the ##N_k## are independent but not identically-distributed geometric random variables. Getting the actual probability distribution of ##S_i## is a challenging problem.
 

Related to Probability Mass Function of 50 collectibles

1. What is a Probability Mass Function (PMF)?

A Probability Mass Function is a statistical tool used in probability theory to describe the probability distribution of a discrete random variable. It assigns probabilities to each possible value that the random variable can take on.

2. How is a PMF calculated for 50 collectibles?

To calculate a PMF for 50 collectibles, you would first need to determine the number of possible outcomes for each collectible (e.g. 50 collectibles would have 50 possible outcomes). Then, you would need to assign a probability to each of these outcomes, making sure that the probabilities add up to 1. This can be done through collecting data or using theoretical probabilities.

3. What is the purpose of using a PMF for 50 collectibles?

The purpose of using a PMF for 50 collectibles is to understand the probability distribution of the different outcomes that could occur when collecting these items. It can also be used to make predictions about the likelihood of certain outcomes and inform decision making.

4. Can a PMF change over time for 50 collectibles?

Yes, a PMF can change over time for 50 collectibles. This could happen if the probability of obtaining certain collectibles changes, or if new collectibles are added to the pool of possibilities. It is important to regularly update the PMF to accurately reflect the current probability distribution.

5. How can a PMF be used in practical applications for 50 collectibles?

A PMF for 50 collectibles can be used in various practical applications, such as predicting the likelihood of completing a collection, determining the optimal strategy for collecting certain items, and analyzing the value and rarity of different collectibles. It can also be used in risk assessment and decision making processes related to collecting these items.

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