Binomial Distribution Statistics Problem

In summary: It is the probability that something has a specific value, in this case the probability that two people have the same sign.
  • #1
blondsk8rguy
1
0

Homework Statement



Estimate the probability that, in a group of five people, at least two of them have the same zodiacal sign. (There are 12 zodiacal signs; assume that each sign is equally likely for any person.)

Homework Equations



P(X=k) = nCk * [tex]p^{k}[/tex] * [tex](1-p)^k{}[/tex]

The Attempt at a Solution



I think that it involves in some way subtracting the probability that everyone has a unique zodiacal sign from 1, but I'm not sure exactly how.
 
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  • #2
Could you possibly tell us a little more about the variables in that formula. "What do C, k, n, and p represent?"
 
  • #3
Look up the birthday problem, it's pretty similar to this isn't it?
 
  • #4
blondsk8rguy said:

Homework Statement



Estimate the probability that, in a group of five people, at least two of them have the same zodiacal sign. (There are 12 zodiacal signs; assume that each sign is equally likely for any person.)

Homework Equations



P(X=k) = nCk * [tex]p^{k}[/tex] * [tex](1-p)^k{}[/tex]

The Attempt at a Solution



I think that it involves in some way subtracting the probability that everyone has a unique zodiacal sign from 1, but I'm not sure exactly how.

Exactly the right approach. How many ways are there to assign a different sign to each person and how many ways to assign any sign to any person. Take the ratio and subtract from 1.
 
  • #5
blondsk8rguy said:

Homework Statement



Estimate the probability that, in a group of five people, at least two of them have the same zodiacal sign. (There are 12 zodiacal signs; assume that each sign is equally likely for any person.)

Homework Equations



P(X=k) = nCk * [tex]p^{k}[/tex] * [tex](1-p)^k{}[/tex]

The Attempt at a Solution



I think that it involves in some way subtracting the probability that everyone has a unique zodiacal sign from 1, but I'm not sure exactly how.
Your formula is incorrect- perhaps a typo. It should be
P(X=k) = nCk * [tex]p^{k}[/tex] * [tex](1-p)^{n-k}[/tex]


Yes, "at least two the same" is the opposite of "all different". Since there are 5 people and you want 5 different signs, both n and k in your binomial coefficient are 5 so that is easy- its just 1. In fact, [itex](1- p)^{5-5}= (1-p)^0= 1[/itex] so it is just "probability of all the same" is [itex]p^5[/itex]. What is p?
 

What is a binomial distribution?

A binomial distribution is a probability distribution that represents the number of successes in a series of independent trials, where each trial has only two possible outcomes (such as success or failure). It is characterized by two parameters: n, the number of trials, and p, the probability of success for each trial.

How is the binomial distribution used in statistics?

The binomial distribution is used to model situations where there are only two possible outcomes, such as in coin flips or medical trials. It allows us to calculate the probability of a certain number of successes in a given number of trials, and is often used in hypothesis testing and confidence intervals.

What is the difference between a binomial distribution and a normal distribution?

A binomial distribution is discrete, meaning that the possible outcomes are countable, while a normal distribution is continuous, meaning that the possible outcomes can take on any value within a certain range. Additionally, a binomial distribution is skewed, while a normal distribution is symmetrical.

What are the assumptions of a binomial distribution?

The assumptions of a binomial distribution include: the trials are independent, there are only two possible outcomes, the probability of success remains constant for each trial, and the number of trials is fixed. Violations of these assumptions can affect the accuracy of the results.

How do you calculate the mean and standard deviation of a binomial distribution?

The mean of a binomial distribution is equal to n*p, where n is the number of trials and p is the probability of success. The standard deviation is equal to the square root of n*p*(1-p). These calculations can be done using a binomial probability calculator or by hand using formulas.

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