Finding the Distribution of Minimum Random Variables in Uniform Distribution?

In summary, we are given n mutually independent random variables that are uniformly distributed on the integers from 1 to k. We are looking for the distribution of the minimum of these variables, Y. Using a trick suggested by the professor, we can determine that the probability of Y being equal to a specific value x is (k-x+1)^n - (k-x)^n / k^n. Additionally, the probability of Xi being greater than or equal to x is (k-x+1)/k, which can be raised to the nth power to determine the distribution of Y.
  • #1
roeb
107
1

Homework Statement



Let X1, X2, ... Xn be n mutually independent random variables each of which is uniformly distributed on the integers from 1 to k. Let Y denote the minimum of the Xi's. Find the distribution of Y.

Homework Equations


The Attempt at a Solution



I can see that P(Xi = j) = 1/K (uniformly distributed), where i = 1, 2, 3, .. n and j = 1, 2, 3, .. k and Y = min (X1, X2, ..., Xn)

So using a 'trick' that my professor told us, {at least x} - {at least x + 1} = {exactly x} -- but shouldn't that be reversed to get "x" or are we assuming that x+1 < x?

My professor also said that (P(Xi>= x))n = ( (k - x + 1)/k )n but I'm having a hard time seeing where this is derived from. Can anyone explain it?

Ultimately, P( Y = x) = ( (k-x+1)^n - (k-x)^n ) / k^n
 
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  • #2
"{at least x} - {at least x + 1} = {exactly x}"

To visualize this pick a specific x for a concrete example: I choose x = 10

at least 10 = 10, 11, 12, 13, ...

at least 11 = 11, 12, 13,...

(at least 10) - (at least 11) = 10

"(P(Xi>= x))n = ( (k - x + 1)/k )n"

Suppose Xi >= x. Of the k total values there are k - x + 1 smaller than x, so
P(Xi < x ) = (k-x+1)/k. Raise both sides to the nth power.
 
  • #3
Understood, thanks!
 

1. What is a statistics distribution?

A statistics distribution is a representation of how data is spread out or grouped together. It shows the frequency of different values or ranges of values in a dataset.

2. What are the different types of statistics distributions?

The main types of statistics distributions are normal distribution, uniform distribution, binomial distribution, and poisson distribution. Other types include exponential, geometric, and chi-square distributions.

3. How is a statistics distribution different from a probability distribution?

A statistics distribution shows the frequency of values in a dataset, while a probability distribution shows the likelihood of a particular outcome occurring in a random experiment. Statistics distributions are based on observed data, while probability distributions are based on theoretical probabilities.

4. How do you determine which statistics distribution to use for a dataset?

The choice of statistics distribution depends on the type of data and the research question being investigated. For example, if the data is continuous and symmetric, a normal distribution may be suitable. If the data is discrete and can only take two values (e.g. success or failure), a binomial distribution may be appropriate.

5. Can you manipulate a statistics distribution?

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