Is |Z| a Positive Normal Distribution?

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SUMMARY

The discussion centers on proving that the absolute value of a standard normal variable, |Z|, follows a positive normal distribution defined by the function ψ(x) = 2φ(x) - 1. Participants highlight the relationship between the cumulative distribution function (CDF) of |Z| and the standard normal CDF, Φ(x). The key insight involves simplifying the expression P(|Z| ≤ x) = P(-x ≤ Z ≤ x) = Φ(x) - Φ(-x) and recognizing that Φ(-x) can be expressed as 1 - Φ(x). This leads to the conclusion that |Z| indeed conforms to the characteristics of a positive normal distribution.

PREREQUISITES
  • Understanding of standard normal distribution and its properties
  • Familiarity with cumulative distribution functions (CDFs)
  • Knowledge of the function φ(x) representing the standard normal distribution
  • Basic skills in probability theory and statistical notation
NEXT STEPS
  • Study the properties of the cumulative distribution function of the standard normal distribution, Φ(x)
  • Learn about transformations of random variables, specifically absolute values of normal distributions
  • Explore the derivation and applications of the positive normal distribution
  • Investigate the implications of the symmetry of the standard normal distribution on its CDF
USEFUL FOR

Students in statistics or probability theory, mathematicians focusing on distribution properties, and anyone interested in understanding the behavior of normal distributions and their transformations.

Proggy99
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Homework Statement


Let \psi(x) = 2\phi(x) - 1. The function \psi is called the positive normal distribution. Prove that if Z is standard normal, then |Z| is positive normal.


Homework Equations





The Attempt at a Solution


I am not really sure where to begin with this. Can anyone provide me a jumping off point, please?

I do know that \phi(-x) = 1 - \phi(x)
and so \phi(x) + \phi(-x) - 1 = 0.
I am not sure how to utilize that or if it is even on the right track. Thanks for any help.
 
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Start with the cumulative distribution function of |Z|

<br /> P(|Z| \le x) = P(-x \le Z \le x) = \Phi(x) - \Phi(-x)<br />

where \Phi is the cdf of the standard normal. How can you simplify \Phi(-x)?
 
Ahhh, that makes perfect sense statdad. I kept trying to factor out 'x' when I looked at it the way you did it and got nowhere so discarded that method. I would substitute that with the equation I put in my first post to get the equation from the definition of positive normal. I just could not come up with that middle step to link the ideas until you put it so plainly. Thanks!


statdad said:
Start with the cumulative distribution function of |Z|

<br /> P(|Z| \le x) = P(-x \le Z \le x) = \Phi(x) - \Phi(-x)<br />

where \Phi is the cdf of the standard normal. How can you simplify \Phi(-x)?
 

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