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What Distribution Is the Coat Hangers Problem Probability?

In a coat hangers probability problem where a fixed number of hangers are selected without replacement from a box containing some bent hangers, what distribution models the number of bent hangers selected, and how is a probability computed?

Subject: Statistics Chapter: Discrete Random Variables and Their Probability Distributions Topic: The Hypergeometric Probability Distribution Answer included
what distribution is the coat hangers problem probability coat hangers probability hypergeometric distribution sampling without replacement discrete random variable probability mass function combinations binomial coefficient
Accepted answer Answer included

Problem

The phrase “what distribution is the coat hangers problem probability” typically refers to a situation where a box contains a fixed number of coat hangers, some bent and some normal, and a sample is drawn without replacement.

Concrete version (fully specified): A box contains \(N=30\) coat hangers, of which \(K=8\) are bent. A student randomly selects \(n=5\) hangers without replacement. Let \(X\) be the number of bent hangers selected.

Tasks: (1) Identify the distribution of \(X\). (2) Write the probability mass function. (3) Compute \(P(X=2)\).

Step 1: Recognize the sampling structure

  • There is a finite population of size \(N\).
  • Each item is one of two types (bent = “success”, normal = “failure”).
  • A sample of size \(n\) is drawn without replacement, so draws are not independent.

This structure matches the hypergeometric distribution.

Step 2: State the hypergeometric model

If \(X\) counts the number of “successes” (bent hangers) in the sample, then:

\[ X \sim \operatorname{Hypergeometric}(N, K, n) \]

Symbol Meaning Value here
\(N\) Total number of coat hangers in the box 30
\(K\) Number of bent (success) hangers in the box 8
\(n\) Number of hangers selected 5
\(X\) Number of bent hangers in the sample \(0,1,2,3,4,5\)

Step 3: Probability mass function

The hypergeometric probability mass function is:

\[ P(X=x)=\frac{\binom{K}{x}\binom{N-K}{n-x}}{\binom{N}{n}} \quad \text{for } \max\!\bigl(0,\,n-(N-K)\bigr)\le x \le \min(n,K) \]

In this coat hangers problem, the support is \(x=0,1,2,3,4,5\).

Step 4: Compute a sample probability \(P(X=2)\)

“Exactly 2 bent hangers” means choosing 2 from the 8 bent and 3 from the 22 normal:

\[ P(X=2)=\frac{\binom{8}{2}\binom{22}{3}}{\binom{30}{5}} \]

Evaluate the combinations:

\[ \binom{8}{2}=28,\quad \binom{22}{3}=1540,\quad \binom{30}{5}=142506 \]

Substitute:

\[ P(X=2)=\frac{28\cdot 1540}{142506} =\frac{43120}{142506} =\frac{3080}{10179} \approx 0.3026 \]

Visualization: population split and the sampled count

Hypergeometric setup for a coat hangers probability problem (without replacement) Population: \(N=30\) Bent \(K=8\) Normal \(N-K=22\) sample \(n=5\) Sample: \(n=5\) with \(X\) bent Example \(X=2\) \(n-X=3\) Probability uses \(\binom{K}{x}\binom{N-K}{n-x}/\binom{N}{n}\).
The count of bent hangers in a sample without replacement is hypergeometric; the diagram shows the finite population split and one example sample count.

Final conclusion

For a coat hangers problem probability question where hangers are selected without replacement from a box with a fixed number of bent hangers, the correct distribution is the hypergeometric distribution, and probabilities follow \[ P(X=x)=\frac{\binom{K}{x}\binom{N-K}{n-x}}{\binom{N}{n}}. \]

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