MHB -7.6.69 Determine the value z^* that...

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The discussion focuses on determining specific z-values that separate different percentages of a standard normal distribution. For the largest 3%, the z-value is 1.88; for the largest 1%, it is 2.33; for the smallest 4%, it is 1.75; and for the smallest 10%, it is 1.28. The cumulative distribution function (CDF) of the standard normal distribution, denoted as Φ(z), is essential for these calculations. The inverse function, Φ^{-1}(p), is used to find the z-scores corresponding to given probabilities. Understanding these concepts is crucial for solving related statistical problems.
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Determine the value $z^*$ that...
a. Separates the largest $3\%$ of all z values from the others
$=1.88$
b. Separates the largest $1\%$ of all z values from the others
$=2.33$
c. Separates the smallest $4\%$ of all z values from the others
$=1.75$
d. Separates the smallest $10\%$ of all z values from the others
$=1.28$

OK just can't seem to find an example of how these are stepped thru
the book answer follows the =
 
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once again $$\Phi(z)$$ is the CDF of the standard normal distribution
you'll need some way to compute the inverse of this function to complete this problem.

a)$$ \Phi(z^*) = 0.97\\ z^* = \Phi^{-1}(0.97)= 1.88079$$

b) $$\Phi(z^*) = 0.99$$

c) $$\Phi(z^*) = 0.04$$

d)$$ \Phi(z^*) = 0.1$$
 
romsek said:
once again $$\Phi(z)$$ is the CDF of the standard normal distribution
you'll need some way to compute the inverse of this function to complete this problem.

a)$$ \Phi(z^*) = 0.97\\ z^* = \Phi^{-1}(0.97)= 1.88079$$

b) $$\Phi(z^*) = 0.99$$

c) $$\Phi(z^*) = 0.04$$

d)$$ \Phi(z^*) = 0.1$$

mahalo I was unaware of the use of that symbol

Screenshot 2021-09-02 11.25.39 AM.png


ok I can see that at 1.88 goes to .97 on table
or using P to z calculator but still what is $\Phi^{-1}$
 
Last edited:
$$\Phi^{-1}(p)$$ is the inverse of $$\Phi(z)$$

If you are given a probability $$p, \Phi^{-1}(p)$$ returns the associated z-score of $$p$$
 
Since [math]\Phi(1.88)= 0.97[/math], [math]\Phi^{-1}(0.97)= 1.88[/math]
 

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