Calculating μ for a Normal Distribution with Given Probability

In summary, the conversation discusses a question about finding the value of μ in a normal distribution with a given mean and variance, and a probability of X being greater than a certain value. The equation used is z=(x-μ)/SD, and after some calculations, the answer of μ=12.9 is achieved by rearranging the equation to μ-10 and using the formula. The conversation also addresses confusion about the use of μ-x instead of x-μ and the possible application of the P(A) = 1- rule, but it does not lead to the correct answer.
  • #1
SolCon
33
1
Hello to all.

Simple question but I'm getting the wrong answer here.

Question:

The random variable X is normally distributed with mean μ and variance 21.0. Given that
P(X > 10.0) = 0.7389, find the value of μ.

The equation we'll use is thus: z=(x-μ)/SD
So, what I did was:

0.64 ([tex]\phi[/tex]0.7389) = (10-μ)/under.root.21
(0.64)(under.root.21)-10=-μ
2.9-10=-μ
-7.1=-μ
μ=7.1

This answer is wrong for some reason and I have no idea why this is so. Any help here is appreciated.
 
Physics news on Phys.org
  • #2
".7389" is the probability that z is less than or equal to .64. You are asked about the probability that a value is larger than 10,
 
  • #3
Thanks for the reply. :approve:

The answer to this question is 12.9. But this was achieved by having in the above equation "μ-10". Multiplying under root 21 with 0.64 then adding 10 will give us this answer. But isn't the formula "x-μ" instead of "μ-x"?

You have said that the prob being asked is greater than 10. But how will this affect the equation (are you driving at the P(A) = 1- rule? If so, I've done that but that does not bring the correct answer either.) ?
 
  • Like
Likes Ramjhun.salman

1. What is a normal distribution?

A normal distribution is a symmetric probability distribution that is commonly seen in nature. It is characterized by a bell-shaped curve and is often used to model real-world phenomena such as height, weight, and test scores.

2. How is a normal distribution defined mathematically?

A normal distribution is defined by two parameters: the mean (μ) and the standard deviation (σ). The mean represents the central tendency of the data, while the standard deviation represents the spread of the data around the mean.

3. What is the significance of μ in a normal distribution?

The value of μ in a normal distribution determines the location of the peak of the bell curve. It is also the average of all the data points and is used to calculate the probability of a given observation occurring within a certain range.

4. How is μ calculated in a normal distribution?

The mean (μ) of a normal distribution is calculated by taking the sum of all the data points and dividing it by the total number of data points. In mathematical notation, it is represented as μ = (x1 + x2 + ... + xn) / n, where x1 to xn are the individual data points and n is the total number of data points.

5. Can μ be negative in a normal distribution?

Yes, μ can be negative in a normal distribution. This means that the peak of the bell curve will be located to the left of the y-axis. However, the data points will still be symmetrically distributed around the mean, following the same bell-shaped curve.

Similar threads

  • Set Theory, Logic, Probability, Statistics
Replies
2
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
1
Views
923
  • Set Theory, Logic, Probability, Statistics
Replies
4
Views
2K
  • Set Theory, Logic, Probability, Statistics
Replies
1
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
6
Views
2K
  • Set Theory, Logic, Probability, Statistics
Replies
2
Views
1K
  • Set Theory, Logic, Probability, Statistics
Replies
30
Views
2K
  • Calculus and Beyond Homework Help
Replies
1
Views
735
  • Set Theory, Logic, Probability, Statistics
Replies
4
Views
3K
  • Set Theory, Logic, Probability, Statistics
Replies
7
Views
469
Back
Top