Binomial Probability Distribution

In summary: Consider that 2% is 2 in 100, so 1 in 100 would be 1%, which is half of 2%. So we might expect a bit less than half of 1%. But you're picking 25 times from 2 million, so there's a lot of chances to get that 1% probability. I hope that helps you understand why the probability looks high.For part b, you have the right idea, but the notation is a bit off. You want to find 1 minus the probability that none of the 25 students received a special accommodation. This is the same as the probability that all of them did not receive special accommodations. So the notation should be:1 - \sum_{x
  • #1
exitwound
292
1

Homework Statement



The College Board reports that 2% of the 2 million high school students who take the SAT each year receive special accommodations because of documented disabilities. Consider a random sample of 25 students who have recently taken the test.

a.) What is the probability that exactly 1 received a special accommodation?
b.) What is the probability that at least 1 received a special accommodation?


Homework Equations



[tex]\begin{pmatrix}
n\\
x\\
\end{pmatrix}p^x(1-p)^{(n-x)}[/tex]

The Attempt at a Solution



a.) [tex]\begin{pmatrix}
25\\
1\\
\end{pmatrix}.02^x(1-.02)^{(25-1)} = .3079[/tex]

30% seems kind of high. If 40,000 students out of 2,000,000 were {success} and chose 25 of the 2,000,000, there's a 30% chance I'd get 1 of the 40,000? That, just seems too high for some reason.

b.) [tex]
\sum_{x=1}^{25}
\begin{pmatrix}
25\\
x\\
\end{pmatrix}.02^x(.98)^{(25-x)}[/tex]

Does this look right? How can I calculate this? I don't believe I have to simplify it, per instructor's orders...but I'm not sure if I have it right to begin with.
 
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  • #2
exitwound said:

Homework Statement



The College Board reports that 2% of the 2 million high school students who take the SAT each year receive special accommodations because of documented disabilities. Consider a random sample of 25 students who have recently taken the test.

a.) What is the probability that exactly 1 received a special accommodation?
b.) What is the probability that at least 1 received a special accommodation?


Homework Equations



[tex]\begin{pmatrix}
n\\
x\\
\end{pmatrix}p^x(1-p)^{(n-x)}[/tex]

The Attempt at a Solution



a.) [tex]\begin{pmatrix}
25\\
1\\
\end{pmatrix}.02^x(1-.02)^{(25-1)} = .3079[/tex]

30% seems kind of high. If 40,000 students out of 2,000,000 were {success} and chose 25 of the 2,000,000, there's a 30% chance I'd get 1 of the 40,000? That, just seems too high for some reason.

b.) [tex]
\sum_{x=1}^{25}
\begin{pmatrix}
25\\
x\\
\end{pmatrix}.02^x(.98)^{(25-x)}[/tex]

Does this look right? How can I calculate this? I don't believe I have to simplify it, per instructor's orders...but I'm not sure if I have it right to begin with.

As far as A is concerned, it looks OK to me... wait for other opinions :\

as far as B is concerned, you can find the probability that zero out of the 25 students get the special accommodation and calculate
1-(zero out of 25)= at least one

they are the complements of each other.

(none)+(at least 1)= 1
 
  • #3
That is exactly what I thought. however, how can you calculate that 0 of 25 are {success}? It would come out as this:

[tex]1-[{
\begin{pmatrix}
25\\
0\\
\end{pmatrix}.02^0(1-.02)^{(25-0)}}]
[/tex]

Do I ignore the 25C0 at the beginning? If I do, I get:

[tex]1-[{(1-.02)^{(25)}}] = 1 - .603 = .397
[/tex]
 
  • #4
25 choose 0 is 1. Intuitively there is only one way to choose 0 things (namely by choosing nothing). But 0! is defined to be 1. Also your part a) is correct. It's only a sample after all.
 
  • #5
exitwound said:
that is exactly what i thought. However, how can you calculate that 0 of 25 are {success}? It would come out as this:

[tex]1-[{
\begin{pmatrix}
25\\
0\\
\end{pmatrix}.02^0(1-.02)^{(25-0)}}]
[/tex]

do i ignore the 25c0 at the beginning? If i do, i get:

[tex]1-[{(1-.02)^{(25)}}] = 1 - .603 = .397
[/tex]
c(25,0)=1
 
  • #6
Ooh. Right. 0!=1. Somehow, that slipped my mind.

Thanks a lot.
 
  • #7
25C0 = 1. There's only one way to select nothing from 25.

Your answer to part a is correct. It may seem high, but it's not. The effect of what seems like small probabilities can build up very quickly.
 

FAQ: Binomial Probability Distribution

What is a binomial probability distribution?

A binomial probability distribution is a statistical model that describes the probability of obtaining a certain number of successes in a fixed number of independent trials, where each trial has only two possible outcomes (success or failure) and the probability of success remains constant. It is often used in experiments or studies where there are only two possible outcomes, such as flipping a coin or testing a new medication.

How is the binomial probability distribution different from other probability distributions?

The binomial distribution is unique because it only considers two possible outcomes and assumes that each trial is independent. Other probability distributions, such as the normal distribution or Poisson distribution, can have multiple outcomes or consider the relationship between events. Additionally, the binomial distribution is discrete, meaning that it only applies to whole numbers, while other distributions can be continuous.

What are the key components of a binomial probability distribution?

There are three key components of a binomial probability distribution: the number of trials (n), the probability of success in each trial (p), and the number of successes (x) that we are interested in. These components are used to calculate the probability of obtaining x successes in n trials using the formula P(x) = nCx * p^x * (1-p)^(n-x), where nCx represents the number of combinations of x successes out of n trials.

How is the binomial probability distribution used in real life?

The binomial probability distribution is used in various fields, such as psychology, biology, and finance, to analyze and make predictions about events or outcomes with only two possible outcomes. For example, it can be used to determine the probability of a certain number of patients responding positively to a new medication, or the likelihood of a certain number of stock market investments being profitable.

What are some limitations of the binomial probability distribution?

One limitation of the binomial distribution is that it assumes each trial is independent, meaning that the outcome of one trial does not affect the outcome of another. This may not always be the case in real life situations. Additionally, it can only be used for discrete data and may not accurately represent continuous data. Finally, the binomial distribution is only applicable to situations with two possible outcomes, so it cannot be used for events with multiple outcomes or more complex relationships between events.

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