Choosing two numbers uniformly

  • Thread starter E'lir Kramer
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In summary: Thank you for the correction! In summary, the question asks for the probability that the sum of two numbers chosen uniformly and without replacement from the set {0,1,...,10}, where the smallest number is also less than or equal to 5, is less than or equal to 10. The answer to this question is 2/3.
  • #1
E'lir Kramer
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This is a solved problem and I am having a hard time working through the answer.

Question . Choose two numbers uniformly but without replacement in {0,1,...,10}. What is the probability that the sum is less than or equal to 10 given that the smallest is less than or equal to 5?

Answer.

Draw a picture of $$\Omega = \left\{ 0,1,...,10 \right\}^{2}\; \backslash \;\left\{(i,i) | i = 0,1,...,10 \right\}$$

Comment. This is easy. (Once I figured out that \ means "complement", as opposed to the last author who was using -). It's a 11x11 grid of dots with the bottom-left to top-right diagonal removed. This immediately tells me, for instance, that [itex]|\Omega| = 11*11 - 11 = 110[/itex].

The outcomes in [itex]\Omega[/itex] all have the same probability. Let also

$$A = \left\{ \omega \;|\; \omega_{1} \neq \omega_{2}, \omega_{1} + \omega_{2} \leq 10 \right\} \quad B = \left\{\omega \;|\; \omega_{1} \neq \omega_{2}, \min\left\{\omega_{1}, \omega_{2}\right\} \leq 5 \right\}$$

The probability we are looking for is [itex]\frac{|A \cap B|}{|B|} = \frac{|A|}{|B|}[/itex].

Starting to get confused here. It looks like the authors are getting the left side of this equation from the definition of conditional probability; [itex]P([A|B]) = P(A \cap B)/P(B)[/itex], and it just so happens that A is fully within B, so [itex]P(A \cap B) = P(A)[/itex]. However, in this author's usage, |X| means "the cardinality of X", and [itex]P(B) \neq |B|[/itex]. However, this kind of makes sense, in a way. Since we are given that the result is in B, B can take the role of the sample space, and the number of ways to achieve the result divided by the size of the sample space does yield the probability we want. So, I'm going to accept this.

Your picture shows that [itex] |A| = 10 + 9 + 8 + ... + 1 = 55 [/itex]...

I don't know about the picture showing this, but reasoning does show this: if [itex]\omega_{1} = 0 [/itex], there are 10 ways to be in A. If [itex]\omega_{1} = 1 [/itex], 9 ways. This logic extends to the given formula .

...and that [itex]|B| = 10x5 + 4x5 = 70 [/itex].

What? I'm completely stopped here. My picture doesn't show that. If I draw a vertical line at (5,0) and a horizontal line at (0,5), then dots in the top right quadrant are the only ones not in [itex]B[/itex], i.e., they are [itex]B^{c}[/itex]. By manually counting I get 20 dots in [itex]B^{c}[/itex], and [itex]|B| = |\Omega| - |B^{c}| = 90[/itex].

Moreover, reasoning confirms this. [itex]B^{c} = |\left\{6,7,...,10\right\}^{2}| - |\left\{(6,6), (7,7),...,(10,10)\right\}| [/itex].



Hence the answer is 55/70.

My answer is 55/90.
 
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  • #2
I get the same solution as you.

One more way to see it (with a sloppy notation, but I think it should be clear):
B is (0,anything) and (1,anything) and ... and (5,anything) and (6 to 10,0) and (6 to 10,1) and ... (6 to 10,5)
In total, 6*10+5*6=90 elements.
 
  • #3
Ohh, thanks. I see his thought process now in his answer. Anyway, we are right, and I just confirmed that in Haskell. So I'll email him with the revision.

Haskell program:

Prelude> length [ (i,j) | i <- [0..10], j <- [0..10], i /= j, (i <= 5 || j <= 5)]
90
 
  • #4
Funny story, but |A| is 60, not 55.

Proof by enumeration:

Prelude> length [ (i,j) | i <- [0..10], j <- [0..10], i /= j, (i + j) <= 10]
60
Prelude> *[ (i,j) | i <- [0..10], j <- [0..10], i /= j, (i + j) <= 10]
[(0,1),(0,2),(0,3),(0,4),(0,5),(0,6),(0,7),(0,8),(0,9),(0,10),(1,0),(1,2),(1,3),(1,4),(1,5),(1,6),(1,7),(1,8),(1,9),(2,0),(2,1),(2,3),(2,4),(2,5),(2,6),(2,7),(2,8),(3,0),(3,1),(3,2),(3,4),(3,5),(3,6),(3,7),(4,0),(4,1),(4,2),(4,3),(4,5),(4,6),(5,0),(5,1),(5,2),(5,3),(5,4),(6,0),(6,1),(6,2),(6,3),(6,4),(7,0),(7,1),(7,2),(7,3),(8,0),(8,1),(8,2),(9,0),(9,1),(10,0)]

The 10 + 9 + 8 + ... + 1 breaks down because when w1 ≥ 6, we don't have to subtract the pairs (6,6) ... (10,10) from our count. They are already subtracted out by virtue of being >10 anyway. Final answer is 60/90 = 2/3
 
Last edited:
  • #5
Ah, good catch.
 

1. How do you choose two numbers uniformly?

To choose two numbers uniformly, you can use a random number generator that generates numbers within a specified range. This ensures that each number has an equal probability of being selected.

2. What is the purpose of choosing two numbers uniformly?

Choosing two numbers uniformly is often used in statistical analysis and simulations to simulate random events or data. It can also be used to generate random coordinates for mapping or graphing.

3. What are the possible outcomes when choosing two numbers uniformly?

The possible outcomes when choosing two numbers uniformly depend on the specified range. For example, if the range is 1-10, the possible outcomes could be any two numbers between 1 and 10, including decimals or negative numbers.

4. Is choosing two numbers uniformly the same as random selection?

Yes, choosing two numbers uniformly is a type of random selection. It ensures that each number has an equal chance of being selected, making the selection process truly random.

5. What are some examples of real-world applications of choosing two numbers uniformly?

Choosing two numbers uniformly is commonly used in gambling, lottery drawings, and simulations in fields such as economics, physics, and biology. It can also be used in computer programming for generating random outcomes in games or simulations.

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