Normal distribution probability question

AI Thread Summary
The discussion revolves around calculating the middle 40% of scores in a normally distributed aptitude test with a mean of 500 and a standard deviation of 100. The user correctly applies the z-score formula to find the corresponding x-values for the middle 40%, arriving at a range of 447.5 to 552.5. Another participant confirms the calculations and method, indicating that the approach is valid. The conversation highlights the use of statistical tables and z-scores in determining probabilities within a normal distribution. Overall, the method used for the calculation is affirmed as correct.
fobster
Messages
3
Reaction score
0
Got a question I need a little bit of help.

Assume the scores on an aptitude are normally distributed with mean=500 and standard deviation=100

What is the middle 40%?

My workings

p(x1≤x≤x2)=p(z1≤z≤z2)

=> p(z1≤z≤z2)=p(z≤z2)-p(z≥z1)=p(z≤z2)-[1-p(z≤z1)]

p(z≤z2)=0.7 p(z≤z1)=0.3
from statistical tables
=> z2= -0.525 z1= 0.525

z1=(x-500)/100=0.525 => x=500+52.5=552.5

z2=(x-500)/100=-0.525 => x=500-52.5=447.5

therefore the middle 40% is between 447.5 and 552.5.

Now my question. Is that the correct method and approach, it is a bonus if I got it right. I only want to check the method really. Thanks.
 
Physics news on Phys.org
I think it's correct.

Normal distribution is given \frac 1 {\sigma \sqrt{\pi}} exp(-(x-\mu)^2/\sigma^2), where \mu is the mean and \sigma is the standard deviation.

I looked at table and center 20% probability is (standard deviation)*(between 0.52 and 0.53)

So your calculation looks fine. :smile:
 
Last edited:
I picked up this problem from the Schaum's series book titled "College Mathematics" by Ayres/Schmidt. It is a solved problem in the book. But what surprised me was that the solution to this problem was given in one line without any explanation. I could, therefore, not understand how the given one-line solution was reached. The one-line solution in the book says: The equation is ##x \cos{\omega} +y \sin{\omega} - 5 = 0##, ##\omega## being the parameter. From my side, the only thing I could...
Back
Top