Calculating Variance in Normal Distribution with Given Percentile

In summary: The solution is 51.3^2 = 2631.69In summary, using the information given about a normal distribution with a mean of 100, a student's test score of 124 at the 68th percentile was used to calculate the variance of the distribution. By first finding the corresponding value of Z in a standard normal table, the standard deviation was then found to be approximately 51.3. The variance was then calculated to be approximately 2631.69.
  • #1
NihalRi
134
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Homework Statement


A student sits a test and is told that the marks follow a normal distribution with mean 100. The student receives a mark of 124 and is told that he is at the 68th percentile. Calculate the variance of the distribution.

Homework Equations


https://lh3.googleusercontent.com/proxy/XW4iFBVEU-T7v_I-U5zV6mo7CvCYxVfS6kbEiAuBBsiEcJWb-P7AHpF6ciRBv4skZW5pqDilEHh9F5zdeCfu0N0ztdfDS_lm-A=w685-h215-nc

The Attempt at a Solution


I replaced 0.68 for f (x) and 100 for μ and 124 for x. I tried to rearange to solve for σ but was unsuccessful only getting as far as,
0.553 = -288/σ^2 - lnσ
I think my approach might be completely wrong, or is there a way of doing this with the aid of a graphic calculator?
 
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  • #2
NihalRi said:

Homework Statement


A student sits a test and is told that the marks follow a normal distribution with mean 100. The student receives a mark of 124 and is told that he is at the 68th percentile. Calculate the variance of the distribution.

Homework Equations


https://lh3.googleusercontent.com/proxy/XW4iFBVEU-T7v_I-U5zV6mo7CvCYxVfS6kbEiAuBBsiEcJWb-P7AHpF6ciRBv4skZW5pqDilEHh9F5zdeCfu0N0ztdfDS_lm-A=w685-h215-nc

The Attempt at a Solution


I replaced 0.68 for f (x) and 100 for μ and 124 for x. I tried to rearange to solve for σ but was unsuccessful only getting as far as,
0.553 = -288/σ^2 - lnσ
I think my approach might be completely wrong, or is there a way of doing this with the aid of a graphic calculator?

Your ##f##-formula is incorrect: is should be
[tex] f(x) = \frac{1}{\sqrt{2 \pi} \delta} e^{- \displaystyle \frac{(x-\mu)^2}{2 \delta^2}} [/tex]
Anyway, that is not relevant for this problem: a percentile is a point on the cumulative distribution, not on the probability density function.

There is no closed-form formula for the cumulative distribution, so you need to use tables of the cumulative, or use appropriate software. Some scientific calculators even have a "normal cumulative" button.
 
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  • #3
NihalRi said:

Homework Statement


A student sits a test and is told that the marks follow a normal distribution with mean 100. The student receives a mark of 124 and is told that he is at the 68th percentile. Calculate the variance of the distribution.

Homework Equations


https://lh3.googleusercontent.com/proxy/XW4iFBVEU-T7v_I-U5zV6mo7CvCYxVfS6kbEiAuBBsiEcJWb-P7AHpF6ciRBv4skZW5pqDilEHh9F5zdeCfu0N0ztdfDS_lm-A=w685-h215-nc

The Attempt at a Solution


I replaced 0.68 for f (x) and 100 for μ and 124 for x. I tried to rearange to solve for σ but was unsuccessful only getting as far as,
0.553 = -288/σ^2 - lnσ
I think my approach might be completely wrong, or is there a way of doing this with the aid of a graphic calculator?

Your formula shows the PDF for the normal distribution with mean μ and SD δ. The percentile of the student's score represents the area under the PDF distribution curve from -∞ to x. For example, the 50th percentile means that x = μ. Like Ray Vickson posted, you'll have to use standard normal tables to find out the SD.
 
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  • #4
SteamKing said:
The percentile of the student's score represents the area under the PDF distributio

∫ f (x)dx=0.68

Where f (x) is the PDF

Will this work as a definite integral from 0 to 124 and I try to solve again for σ ?
Well this seemed like it would work until I actually tried to integrate it:)
 
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  • #5
NihalRi said:
∫ f (x)dx=0.68

Where f (x) is the PDF

Will this work as a definite integral from 0 to 124 and I try to solve again for σ ?
No, that's not how the standard normal tables are constructed.

The standard normal distribution has μ = 0 and δ = 1.0. In order to accommodate normal distributions with other values of μ and δ, a transformation formula is used:

##Z = \frac{x-μ}{δ}##

The total area under the standard normal distribution curve is

##\int_{-∞}^{+∞} f(Z)dZ = 1.0##,

but since the curve is symmetrical about μ = 0

##\int_{-∞}^0 f(Z)dZ = 0.5##

Knowing the value of the cumulative distribution, you want to find Z which corresponds to that amount from a standard normal table, like this one:

https://www.mathsisfun.com/data/standard-normal-distribution-table.html

Once you find the correct Z value, then using the student's score and the mean of the distribution, you should be able to work back and solve for the S.D., δ.
 
  • #6
So I set it up so that
P (X≤124) = 0.68
and
P (Z≤(124-100)/σ)
Using invNorm on my calculator for the standard (z) distribution I found
(124-100)/σ≈0.468
σ≈51.3
Variance = 10051
Nice :)

Thank you
 
  • #7
NihalRi said:
So I set it up so that
P (X≤124) = 0.68
and
P (Z≤(124-100)/σ)
Using invNorm on my calculator for the standard (z) distribution I found
(124-100)/σ≈0.468
σ≈51.3
Variance = 10051
Nice :)

Thank you
Everything looks OK, except the variance should be equal to σ2. IDK how you got 10051.
 
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  • #8
SteamKing said:
Everything looks OK, except the variance should be equal to σ2. IDK how you got 10051.
Your right, I must have put the wrong number in the calculator.
 

FAQ: Calculating Variance in Normal Distribution with Given Percentile

What is a normal distribution problem?

A normal distribution problem is a statistical problem that involves a set of data that follows a bell-shaped curve, where most of the data is centered around the mean and tapers off on either side. It is also known as a Gaussian distribution.

What is the formula for calculating the probability of a normal distribution?

The formula for calculating the probability of a normal distribution is: P(x) = (1/σ√2π) * e^(-(x-μ)^2/2σ^2), where μ is the mean, σ is the standard deviation, and e is the base of the natural logarithm.

What is the 68-95-99.7 rule in a normal distribution?

The 68-95-99.7 rule, also known as the empirical rule, states that in a normal distribution, approximately 68% of the data falls within one standard deviation of the mean, 95% falls within two standard deviations, and 99.7% falls within three standard deviations.

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

A standard normal distribution is a specific type of normal distribution with a mean of 0 and a standard deviation of 1. A normal distribution can have any mean and standard deviation, and the formula for calculating its probability is adjusted accordingly.

How is a normal distribution used in real life?

Normal distribution is commonly used in real life to model natural phenomena such as height, weight, and IQ scores. It is also used in quality control, finance, and other areas of research to analyze and make predictions based on data.

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