Statistics: Standard Normal Distribution

In summary, to find the z value that corresponds to a given area under the normal distribution curve, use a table or calculator to find the z-score that corresponds to that area. For areas to the left or right of the mean, simply look up the corresponding area in the table and find the corresponding z value. For areas between two values, add the corresponding z values. Make sure to check the table for the correct decimal values for the area.
  • #1
shawnz1102
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Homework Statement


Find the Z value that corresponds to the given area.
[PLAIN]http://img163.imageshack.us/img163/3785/problem1v.jpg

The Attempt at a Solution


What I did was go to Table E and find the closest number to 0.0166 which was 0.0160, and the Z numbers were 0.04 and 0.0. I then added them up together to get the answer of -0.04 (negative since it's less than 0) but it's wrong. The actual answer was: -2.13. I'm suspecting it's because the area is negative infinite to Z, and that's where I messed up at. Normally if it's between the median (which is 0) and Z, i would just add up both numbers.

Therefore, how do I solve this problem if the area is between infinite to Z?

2. Homework Statement
Find the z value to the left of the mean so that 98.87% of the area under the distribution curve lies to the right of it.

I didn't understand the wording of this problem at all, but I did give my attempt at drawing the graph (not sure if it's correct).
[PLAIN]http://img42.imageshack.us/img42/6641/problem2t.jpg

Actual Answer
The answer of this problem is: -2.28Please help!
 
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  • #2
I have no idea what your Table E contains, but the area under the normal distribution is given by

[tex]\Phi(z) = \frac{1}{\sqrt{2\pi}} \int_{\infty}^z e^{-x^2} dx = \frac{1}{2} \left(1+\text{erf}\left(\frac{z}{\sqrt{2}}\right)\right), [/tex]

where [tex]\text{erf}(t)[/tex] is the error function. The error function can be computed by Wolfram Alpha or looked up in tables.
 
  • #3
1) I'm not sure what table you're using but it should be one like this http://www.math.uh.edu/~bekki/CUIN%206342/zscoretable.pdf I suspect you're either using the wrong table or reading it wrong.

What the chart shows is the z-score on the left (up to first decimal) and top (second decimal). The numbers in the body of the chart show the area under the normal distribution curve less than the indicated z-score. This is the same as saying the area to the left of the z-score.

For example, say you were asked to find the z-score for which 0.54% of the area under the normal distribution curve lies to the left. The first thing to notice is that .54% = 0.0054. Then you look for 0.0054 in the body of the table. Once you find it, look at the corresponding value in the left-most column first to get -2.5 then look at the corresponding value in the top row to get .05. So the z-score that answers the question is -2.55

Apply the same methodology to your question to get the answer.

2) No, your interpretation is off. In some ways this is just the opposite of the first question where it was effectively asking you for the z value to the left of the mean so that 1.66% of the area under the distribution curve lies to the left of it. The "to the left of the mean" part indicates that the z value will be negative.

So your diagram should be shaded red all the way to positive infinity. What you need to figure out is what area is to the left of the required z if 98.87% is to the right. Once you have that area you can do what you did in 1) to get the answer.
 
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FAQ: Statistics: Standard Normal Distribution

What is the Standard Normal Distribution?

The Standard Normal Distribution is a type of probability distribution that is often used in statistics to represent a population of data that follows a bell-shaped curve. It is also known as the Z-distribution and has a mean of 0 and a standard deviation of 1.

How is the Standard Normal Distribution different from other normal distributions?

The Standard Normal Distribution is unique because it has a mean of 0 and a standard deviation of 1, while other normal distributions can have different means and standard deviations. This makes it a useful tool for comparing and analyzing data from different populations.

Why is the Standard Normal Distribution important in statistics?

The Standard Normal Distribution is important because it allows us to make inferences and predictions about a population based on a sample of data. It is also used in many statistical tests and calculations, such as the z-test and confidence intervals.

How do you calculate probabilities using the Standard Normal Distribution?

To calculate probabilities using the Standard Normal Distribution, we use a table or a statistical calculator. The table shows the area under the curve for different z-scores, which represent the number of standard deviations from the mean. The calculator can directly calculate the probabilities based on the z-score or the area under the curve.

What is the relationship between the Standard Normal Distribution and the Central Limit Theorem?

The Central Limit Theorem states that the sampling distribution of the sample means from any population will approach a normal distribution as the sample size gets larger. This means that if we take multiple samples from a population and calculate their means, the distribution of those means will be approximately a Standard Normal Distribution. This is why the Standard Normal Distribution is often used in statistics to make inferences about a population based on a sample of data.

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