Binomial Distribution Probability Problem

It's just 0.7 multiplied by itself 3 times and then multiplied by 0.3. So the answer is 0.1029.In summary, the probability of the first woman being reached on the fourth call in a random selection of 30 people from a mailing list of 70% males and 30% females for a scuba-diving agency is 0.1029. This can be calculated by multiplying the probability of the first three calls being males (0.7 * 0.7 * 0.7) and then the probability of the fourth call being a female (0.3).
  • #1
mkir
10
0

Homework Statement


The mailing list of an agency that markets scuba-diving trips to the Florida Keys contains 70% males and 30% females. The agency calls 30 people chosen at random from its list.

What is the probability that the first woman is reached on the fourth call? (That is, the first 4 calls give MMMF.)

Homework Equations


P(x=k) = (n choose k)p^k(1-p)^(n-k)


The Attempt at a Solution


since they want MMMF does it make sense to do just go

.7 * .7 * .7 * .3 and then divide by 4C1 =4

.1029/4
=.025725
 
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  • #2
This is not a binomial distribution problem - in a binomial distribution you are interested in the total number of "successes", but not the order in which they are obtained, or the exact trial on which the first success is obtained.

You could use the multiplication rule, as you did at the end of your post (don't divide by anything), but there is another probability distribution that fits this type of problem - do you know what that other distribution is?
 
  • #3
No, I don't know what the other distribution is.
 
  • #4
Actually, you don't have to worry about either kind of distribution for this particular question. In order that we get "MMMF" the result must be in that particular order.
What is the probability that the first call be to a man? What is the probability that the second call be to a man? What is the probability that the third call be to a man? What is the probability that the fourth call is to a woman? Now multiply those four probabilities together.
 
  • #5
As Halls says, and I mentioned, you don't need the other formula, as you've already done the work in your first post.
 
  • #6
Thanks guys, I get it now.
 

1. What is the binomial distribution probability problem?

The binomial distribution probability problem is a mathematical concept that deals with calculating the probability of a certain number of successes in a fixed number of independent trials, given a specific probability of success for each trial. It is commonly used in statistics and probability theory to model real-world situations.

2. How is the binomial distribution probability problem different from other probability problems?

The binomial distribution probability problem is different from other probability problems in that it deals with a specific number of trials and a fixed probability of success for each trial. Other probability problems may involve continuous variables, such as rolling a dice, whereas the binomial distribution problem deals with discrete variables, such as flipping a coin.

3. What are the key components in solving a binomial distribution probability problem?

The key components in solving a binomial distribution probability problem are the number of trials, the probability of success for each trial, and the desired number of successes. These values are used in the binomial probability formula to calculate the probability of achieving the desired number of successes in the given number of trials.

4. How can the binomial distribution probability problem be applied in real life?

The binomial distribution probability problem can be applied in real life in many situations, such as predicting the outcome of a sports game or election, estimating the success rate of a marketing campaign, or determining the likelihood of a certain disease occurring in a population. It can also be used to model random events, such as coin tosses or card draws.

5. What are some common misconceptions about the binomial distribution probability problem?

One common misconception about the binomial distribution probability problem is that it can only be used for two outcomes, success and failure. In reality, it can be used for any number of outcomes, as long as the probability of success remains constant for each trial. Another misconception is that the trials must be independent, when in fact they can be dependent as long as the probability of success remains constant.

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