Statisitics - Random Variables

In summary, the probability that k elk are tagged after 5 elk are captured is 1/5, and this can be calculated using a hypergeometric distribution. This is because each captured elk has a different probability of being tagged based on the previous captures.
  • #1
tjackson
5
0

Homework Statement



There is a population of 30 elk. 6 elk are captured, tagged and then released into the wild. Then later 5 elk are captured, what is the probability that k elk are tagged?

Homework Equations



p=6/30 = 1/5P = [itex]\stackrel{n}{k}[/itex] * pk * (1-p)k

[itex]\stackrel{n}{k}[/itex] is n choose k

The Attempt at a Solution



plug in the values.

but the big question I have is: Is this a binomial RV?
 
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  • #2
I think this would be hypergeometric.
 
  • #3
to elaborate, the way you have it, as a binomial, would mean that each deer caught has a 6/30 chance of being tagged. but this is not the case. if you catch a deer and it is tagged, then there are 24 untagged deer and 5 tagged deer remaining. so on your next catch, you would a 5/29 chance of catching a tagged deer. but you can use a hypergeometric distribution on this to make it a little easier.
 

FAQ: Statisitics - Random Variables

1. What is a random variable?

A random variable is a numerical measurement of a random event or outcome. It is represented by a letter, such as X or Y, and can take on different values based on the probability of the event occurring.

2. What is the difference between a discrete and continuous random variable?

A discrete random variable can only take on a finite or countable number of values, while a continuous random variable can take on any value within a certain range. For example, the number of children in a family would be a discrete random variable, while the weight of a person would be a continuous random variable.

3. How do you calculate the expected value of a random variable?

The expected value of a random variable is calculated by multiplying each possible value by its corresponding probability and then summing all of these products. For example, if X is a random variable with values 1, 2, and 3 and probabilities 0.3, 0.4, and 0.3 respectively, the expected value would be (1*0.3) + (2*0.4) + (3*0.3) = 2.

4. What is the role of a probability distribution in random variables?

A probability distribution is a function that assigns probabilities to each possible value of a random variable. It allows us to understand the likelihood of different outcomes occurring and make predictions based on these probabilities.

5. Can a random variable have a negative value?

Yes, a random variable can have negative values. For example, the change in stock price from one day to the next would be a random variable that could take on negative values.

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