Caculate the probability using a binomial distribution

In summary, the conversation discussed using a binomial distribution to calculate the probability of having at least 5 people agree in a mini-survey with 10 people, with a given percentage of agreement and uncertainty. The correct distribution to use in this case is the binomial distribution, as each trial has two possible outcomes and can be described by a Bernoulli random variable.
  • #1
Cyannaca
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Ok so I have a problem I am not sure of the method I should use. In a recent survey, 60% of the population disagreed with a given statement, 20% agreed and 20% were unsure. Find the probability of having at least 5 person who agree in a mini-survey with 10 people.

I tried to caculate the probability using a binomial distribution with n=10, p=0,2 agree and 1-p = 0,8 who either agree or are unsure, and

P(X) = (n!/ (k!(n-k)!)) (p^x) ((1-p) ^(n-x))

I added p(5), p(6)... p(10) and I got p(total) = 0,0328

Is it right to use a binomial distribution in this case?
 
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  • #2
Yes, that is the correct distribution to use.
 
  • #3
Yes. The number of people agreeing with the statement in n trials is random variable with a binomial probability distribution. This is because each individual event or trial has two possible outcomes (agreement or not agreement, if you choose to group them that way), and as a result is described by a Bernoulli random variable.
 
  • #4
Thank you!
 

FAQ: Caculate the probability using a binomial distribution

What is a binomial distribution?

A binomial distribution is a probability distribution that represents the possible outcomes of a series of independent trials, where each trial has two possible outcomes (usually referred to as "success" and "failure") and the probability of success remains constant for each trial.

How is the binomial distribution used in calculations?

The binomial distribution is used to calculate the probability of a certain number of successes (or failures) occurring in a given number of trials, given a specific probability of success for each trial.

What is the formula for calculating the probability using a binomial distribution?

The formula for calculating the probability using a binomial distribution is P(x) = (nCr) * p^x * (1-p)^(n-x), where n is the number of trials, x is the number of successes, and p is the probability of success for each trial.

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

A binomial distribution is discrete, meaning that it deals with specific outcomes, while a normal distribution is continuous, meaning that it deals with a range of outcomes. Additionally, a binomial distribution is used for a fixed number of trials, while a normal distribution is used for a continuous variable.

How do you interpret the results of a binomial distribution calculation?

The result of a binomial distribution calculation is the probability of a certain number of successes occurring in a given number of trials. This probability can be interpreted as the likelihood of obtaining that specific outcome in a series of independent trials with the given probability of success.

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