Normal Self-Product Distribution

In summary, the conversation is about finding the normal self-product distribution in the case of a non-zero mean and standard deviation. One person suggests using the fact that any normal distribution can be expressed in terms of a standard normal distribution, while the other person asks for an equation to do so.
  • #1
natski
267
2
Hi all,

I am trying to evaluate the distribution of a normal distribution producted with itself. On http://mathworld.wolfram.com/NormalProductDistribution.html there is a page about the product distribution in the case of two normals distributions of different standard deviations but the same mean of zero.

I was hoping someone had derived the normal self-product distribution in the case of a mean not equal to zero and a standard deviation not equal to zero. Does anyone know how to do this or where I should look?

Cheers,

Natski
 
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  • #2
Any normally distributed random variable can be expressed in terms of a standard normal random variable; does that help?
 
  • #3
It might do... do you have an equation of how to express a general normal distribution in terms of the standard normal distribution?
 
  • #4
If P is a distribution with mean [itex]\mu[/itex] and standard deviation [itex]\sigma[/itex], then [itex]z= (x- \mu)/\sigma[/itex] has the standard normal distribution.
 

FAQ: Normal Self-Product Distribution

What is a Normal Self-Product Distribution?

A Normal Self-Product Distribution is a probability distribution that is the result of multiplying two independent and identically distributed random variables with a normal distribution. It is also known as a Product Normal Distribution or Normal Multiplicative Distribution.

How is a Normal Self-Product Distribution different from a normal distribution?

A Normal Self-Product Distribution is different from a normal distribution in that it is a result of multiplying two normal distributions together, rather than just one. This means that the resulting distribution will have a different shape and mean compared to a single normal distribution.

What are the characteristics of a Normal Self-Product Distribution?

A Normal Self-Product Distribution is a continuous distribution with a mean of 0 and a standard deviation of 1. It has a bell-shaped curve similar to a normal distribution, but with heavier tails. It is also symmetric around the mean.

What are some real-world applications of a Normal Self-Product Distribution?

A Normal Self-Product Distribution is commonly used in finance and economics to model the behavior of stock prices, as well as in insurance to model loss distributions. It is also used in biology and genetics to model the distribution of traits in offspring.

How is a Normal Self-Product Distribution calculated?

To calculate a Normal Self-Product Distribution, you need to know the mean and standard deviation of the two independent normal distributions that are being multiplied together. The resulting distribution can be found by multiplying the means and adding the variances of the two distributions.

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