Solving Probability Problems with Discrete Distributions

In summary: This is (x/16)^10. Now you have to multiply by the number of ways you can choose 10 boys from x boys, and then by the number of ways to choose 10 boys from 16 students.In summary, to find the number of boys among the 16 students, we can use the formula (x/16)^10 * (xC10 / 16C10) = 3/364, where x represents the number of boys. This can be solved using algebra or trial and error to find that x is approximately 12.
  • #1
chrisyuen
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Homework Statement



At a school sports day, the timekeeping group for running events consists of 1 chief judge, 1 referee and 10 timekeepers. The chief judge and the referee are chosen from 5 teachers while the 10 timekeepers are selected from 16 students.

(a) How many different timekeeping groups can be formed?
(b) If it is possible to have a timekeeping group with all the timekeepers being boys, what are the possible numbers of boys among the 16 students?
(c) If the probability of having a timekeeping group with all the timekeepers being boys is 3 / 364, find the number of boys among the 16 students.

(Answers:
(a) 160160;
(b) 10, 11, 12, 13, 14, 15, 16
(c) 12)

Homework Equations



Formulae for Bernoulli, Binomial, Geometric & Poisson Distributions

The Attempt at a Solution



I don't know how to solve part (c) of the question.

I tried:

xC10 / 16C10 = 3 / 364

and x can be found as 12.

I don't know if the above method is correct or not.

However, the question should be solved using the distribution formulae.

Another attempt:

x: number of boys within the 16 students

P(Boys) = x / 16

16C10 (x / 16)10 (1 - x / 16)6 = 3 / 364

But the x found is not correct.

Can anyone tell me how to solve it?

Thank you very much!
 
Last edited:
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  • #2
I think the second attempt is wrong, because you are using the binomial distribution there (why doesn't it apply?)

The first approach, although possible not worked out entirely correct, seems better. So let x be the number of boys in 16 students. You have to choose 10 students from the 16. What is the probability that they are all boys?
 

1. What is a discrete distribution?

A discrete distribution is a statistical distribution that describes the probability of obtaining a certain outcome when the possible outcomes are countable and finite. These distributions are characterized by a set of distinct values and their corresponding probabilities.

2. How is a discrete distribution different from a continuous distribution?

Unlike a discrete distribution, a continuous distribution describes the probability of obtaining a certain outcome when the possible outcomes are infinite and uncountable. This means that the values in a continuous distribution can take on any real number within a given range, while the values in a discrete distribution are limited to a finite set.

3. What are some examples of discrete distributions?

Some common examples of discrete distributions include the binomial distribution, the Poisson distribution, and the geometric distribution. These distributions are often used to model phenomena such as the number of successes in a series of independent trials, the number of events occurring in a fixed time interval, and the number of trials needed to achieve a certain outcome.

4. How are discrete distributions used in real-world applications?

Discrete distributions are widely used in various fields, including finance, engineering, and biology. For example, the binomial distribution is used in risk assessment and option pricing, the Poisson distribution is used in queueing theory and reliability analysis, and the geometric distribution is used in genetics and epidemiology.

5. How are discrete distributions calculated and analyzed?

The calculation and analysis of discrete distributions involve various techniques and methods, such as probability mass functions, cumulative distribution functions, and moments. These tools help to determine the probabilities of specific outcomes, the expected value and variance of the distribution, and the shape and characteristics of the distribution's graph.

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