Lee missed the lesson on normal distribution and needs to do his homework. Explain to Lee how to use the mean and standard deviation of a normal distribution to determine the top 6% of the population.
@kropot72
A standard normal distribution table can be used to find the top 6% of the population. First it is necessary to use the table to find the z-score that gives a cumulative probability of 1.00 - 0.06 = 0.94. Can you do that step?
what step am I doing? looking for the z-score?
Yes. You need to use the table in reverse. There is a suitable table here: http://www.math.bgu.ac.il/~ngur/Teaching/probability/normal.pdf Look for a cumulative probability close to 0.940, and then find the corresponding value of z-score.
I have a table handy and it's 0.82639
What do I do have after that?
No, you did not use the table in reverse. You found the cumulative probability for a z-score of 0.940. We already have the cumulative probability, it is 0.9400. We need to find the z-score that gives such a value of cumulative probability.
I'm sorry but I don't understand. What's the reason for 0.82639?
Please wait 10 minutes. I am having a meal. 0.82639 does not have any use.
Lets try using the table in reverse to find the z-score that gives a cumulative probability of 0.5000. Can you do that ?
Sorry, my computer was acting weird
Ok
So in reverse. Would it be 1.55 because the closet I found was 0.93943
Yes that is the z-score for a cumulative probability of 0.9400. Next, to find the required value of the random variable X, we use the formula: \[\large z=\frac{X-\mu}{\sigma}\] giving \[\large 1.55=\frac{X-\mu}{\sigma}\]
Now it is necessary to rearrange the equation to find X in terms of mu and sigma.
How do I found it?
this is confusing
\[\large X-\mu=1.55 \sigma\] Therefore \[X=1.55 \sigma+\mu\]
Ok. What Do I do? Am i plugging 0.6 in x?
Just forget it. I'm not really understanding and sorry for wasting your time. I'll give you a metal. Thank you
The solution is the equation for X. Values of the variable above X are in the top 6% of the population. Just plug the values of the population mean (mu) and population standard deviation (sigma) into the equation: \[\large X=1.55 \sigma + \mu\]
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