Probability of X > Y in Normal Distributions & Sampling Bottle Weights

In summary, the conversation discusses two normal distributions and their probabilities, as well as a formula for finding the probability of a randomly chosen bottle weighing less than a certain amount. It is concluded that the probability can be calculated using a formula similar to that used for coin-tossing with a binomial distribution.
  • #1
Maybe_Memorie
353
0

Homework Statement



If we were to have two normal distributions, say X and Y, which are the scores of students on a test or something, a is the score of a student from X and b is the score of a student from Y, what is the probability that a randomly selected student from X will score more than a randomly selected student from Y, i.ie what's the probability that a>b, or something like a>b+10?
Both means and SDs given.



Also, if we have a normal distribution, say for weights of bottles of something, and we know that A is the probability that a randomly chosen bottle will weigh less than X, and we then take a sample of say 6 bottles, and we want to find the probability that 2 or less will weigh less than X, is it just 6C0(1-X)^6 + 6C1(X)(1-X)^5 + 6C2(X)^2(1-X)^4
or do I have to standardise again for the population of 6 bottles?


Thanks! :smile:
 
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  • #2
Maybe_Memorie said:

Homework Statement



If we were to have two normal distributions, say X and Y, which are the scores of students on a test or something, a is the score of a student from X and b is the score of a student from Y, what is the probability that a randomly selected student from X will score more than a randomly selected student from Y, i.ie what's the probability that a>b, or something like a>b+10?
Both means and SDs given.



Also, if we have a normal distribution, say for weights of bottles of something, and we know that A is the probability that a randomly chosen bottle will weigh less than X, and we then take a sample of say 6 bottles, and we want to find the probability that 2 or less will weigh less than X, is it just 6C0(1-X)^6 + 6C1(X)(1-X)^5 + 6C2(X)^2(1-X)^4
or do I have to standardise again for the population of 6 bottles?


Thanks! :smile:

Is this a homework problem? What have you done on it so far? Where are you having trouble?

RGV
 
  • #3
Ray Vickson said:
Is this a homework problem? What have you done on it so far? Where are you having trouble?

RGV

It's not homework, just me doing revision before going back to university in september.

The first one is a problem I came across in a very old exam paper, and don't know where ti begin.

The second one I just need a yes or no answer.
 
  • #4
What kind of distribution is the difference of 2 independent normal distributions?
 
  • #5
I like Serena said:
What kind of distribution is the difference of 2 independent normal distributions?

Normal with mean u1 - u2 and variance V1 + V2
 
  • #6
Wait, think I get it, find the difference as a normal distribution, and then the probability that this is greater than zero for the probability one is bigger than the other?
 
  • #7
Yep! :smile:
 
  • #8
As for the second part of your question.

You have an A which is a probability, and you have an X which is an amount.
You thought up a formula for a probability, which contains X, but does not contain A.
Since X is not a probability, isn't it kind of unlikely that you can use it in a formula where a probability is expected? :confused:
 
  • #9
Sorry! Should have been 6C0(1-A)^6 + 6C1(A)(1-A)^5 + 6C2(A)^2(1-A)^4
 
  • #10
All right. :smile:
Then I'll just say yes, although I do not understand what you mean by "standardize for the population of 6 bottles".
 
  • #11
I like Serena said:
All right. :smile:
Then I'll just say yes, although I do not understand what you mean by "standardize for the population of 6 bottles".

I mean do i treat the six bottles as a new normal population, find the z value for X, and a new probability that a bottle chosen from these will be less than X?
 
  • #12
Ah, now I understand.

Well, did you open the bottles and mix them?
Or did you calculate the mean weight of the 6 bottles and compare that?
 
  • #13
If the 6 bottles are drawn independentally (say, from a large population) you just have a coin-tossing type problem. Each bottle, independent of the others, has a probability 'A' of weighing more than some fixed weight w (you called it X, but I prefer to use the convention that capital letters are random variables, while small letters are given numbers). This is like the problem of getting 3 heads in 6 coin tosses, where each toss has Pr{heads} = A.

RGV
 
  • #14
I like Serena said:
Ah, now I understand.

Well, did you open the bottles and mix them?
Or did you calculate the mean weight of the 6 bottles and compare that?

I think I'm starting to confuse myself...

But basically, if i take 6 bottles from a population, and in this population the probability that a randomly chosen bottle weighs less than X is A,
the probability that 2 of the 6 bottles weighs less than X is the expression i gave above?
 
  • #15
Maybe_Memorie said:
I think I'm starting to confuse myself...

But basically, if i take 6 bottles from a population, and in this population the probability that a randomly chosen bottle weighs less than X is A,
the probability that 2 of the 6 bottles weighs less than X is the expression i gave above?

I already said yes and I'm not changing my answer now! :wink:
As RGV already said, it's basically a coin-tossing problem with a binomial distribution, which is what you wrote down.
 
  • #16
Thanks to both of you! :smile:
 

Related to Probability of X > Y in Normal Distributions & Sampling Bottle Weights

1. What is the significance of comparing the probability of X > Y in normal distributions?

Comparing the probability of X > Y in normal distributions allows us to determine the likelihood of one variable being greater than another in a given sample. This can help us to understand the relationship between two variables and make predictions about their behavior.

2. How is probability calculated in normal distributions?

In normal distributions, probability is calculated using the standard normal distribution, which is a bell-shaped curve that represents the probability distribution of a continuous random variable. The area under the curve represents the probability of a given event occurring.

3. What is the relationship between normal distributions and sampling bottle weights?

Normal distributions are often used to model the weight of objects, such as sampling bottles. This is because many natural phenomena, including weight, tend to follow a normal distribution. By understanding the probability of different weights in a normal distribution, we can make predictions about the weight of sampling bottles and other objects.

4. How does sampling affect the probability of X > Y in normal distributions?

The size of the sample can affect the probability of X > Y in normal distributions. Generally, as the sample size increases, the probability of X > Y decreases, as the distribution becomes more representative of the population. However, the specific relationship between sample size and probability can vary depending on the variables being studied.

5. How can the probability of X > Y in normal distributions be used in practical applications?

The probability of X > Y in normal distributions has many practical applications, such as in quality control processes. By understanding the probability of certain values, we can determine if a sample falls within an acceptable range and make decisions based on that information. This can be particularly useful in industries that rely on consistent and accurate measurements, such as pharmaceuticals or manufacturing.

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