Question bout normal distribution:

In summary, the probability of a next shipment not overflowing the storage space is 1 - Pr(-\infty < z < a).
  • #1
semidevil
157
2
so w/ the normal distribution, to find the area between 2 numbers, say [tex] P(a \leq Z \leq b), [/tex], I need to split this up into 2:

[tex]P(-\infty < z \leq b) - P(-\infty < z < a). [/tex]

my question is, why is it not [tex]P(a < z < +\infty) [/tex]?
 
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  • #2
You could do it that way, if you had tables of values for [itex]P(a < z < +\infty)[/itex], but mostly things are tabulated the other way.

Also:

[tex]P(a < z < +\infty) = 1 - Pr(-\infty < z < a)[/tex]
 
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  • #3
James R said:
You could do it that way, if you had tables of values for [itex]P(a < z < +\infty)[/itex], but mostly things are tabulated the other way.

Also:

[tex]P(a < z < +\infty) = 1 - Pr(-\infty < z < a)[/tex]


so I'm getting confused. I have a question regarding storage space and shipment. they are asking what is the probability that the next shipment will be enough, but at the same time, not overflow the storage space.

so basically [tex] a < z < b [/tex]. so in my problem, it has to be [tex]1279.5 \leq Z < 1310.5 [/tex]

so first, I break it up, and do [tex] 1279.5 < Z < \infty[/tex].

on the second part, do I do [tex] -\infty < z < 1310.5 [/tex] or do I do 1279.5 < z < 1310.5 [/tex]

to me, I think the second one is right...but the way the book is doing it, it seems like it is sayingi f I want to know between a and b, I need to -inf < z < b and also -inf < z < a, which doesn't make that much sense...
 
  • #4
i f I want to know between a and b, I need to -inf < z < b and also -inf < z < a, which doesn't make that much sense...

Maybe there's a way to use those two quantities to determine what you want to know.
 
  • #5
Think of the probability as the area under the bell curve. You want the area between a and b. You have the area between negative infinity and a, and between negative infinity and b. So...
 

FAQ: Question bout normal distribution:

What is a normal distribution?

A normal distribution is a probability distribution that is bell-shaped and symmetrical around the mean. It is characterized by its mean and standard deviation, and many natural phenomena and statistical data follow a normal distribution.

How is a normal distribution different from other distributions?

A normal distribution is unique in that it is the only distribution where the mean, median, and mode are all equal. Additionally, it is the only distribution that is completely defined by its mean and standard deviation.

How can I identify if my data follows a normal distribution?

The best way to determine if your data follows a normal distribution is by creating a histogram or a normal probability plot. If the histogram is bell-shaped and the points on the probability plot fall close to a straight line, then the data is likely to follow a normal distribution.

What are some common uses of the normal distribution?

The normal distribution is widely used in statistical analysis and data modeling. It is used to describe and analyze data in various fields, such as economics, psychology, biology, and more. It is also used in quality control and decision-making processes.

Can a normal distribution have a negative mean or standard deviation?

No, a normal distribution cannot have a negative mean or standard deviation. The mean represents the central value of the distribution, and the standard deviation represents the spread of the data around the mean. Both of these values must be positive in a normal distribution.

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