Normal and Standard normal distributed variable

[johny_5]

What is the benefit of switching from a normal distributed variable to standard normally distributed variable ?

[johny_5]

Please help, this is a question from my homework for tomorrow :S

[Gagramil]

Normal ~ N (mu, sigma)
Standard normal ~N(0,1)

I guess.

[johny_5]

Yes, i know this, but what is the benefit of the standart normally distributed variable ?
In which cases is better to use it ?

[Gagramil]

Well, in the standard normal case you will know its attributes which is an obvious advantage.

Example: I had a time series with prices from different forward contracts that I was gonna apply some technical trading rules to (e.g. moving average). The problem was that different contracts can have different "levels" of prices (e.g. the price at the end of contract t can be 100 and the price at the beginning of contract t+1 be 300). By normalizing within contracts they will all be ~N(0,1) and therefore the problem of different price levels is removed, thus creating a "smooth" price-series.

[Dason]

We have tables to calculate probabilities for the standard normal. You won't find a table for a general normal distribution. Thus if you convert your normal to a standard normal you can actually do tests and such with it. With software this is becoming a non-issue but it was a big issue when such software wasn't freely available.

[johny_5]

We have tables to calculate probabilities for the standard normal. You won't find a table for a general normal distribution. Thus if you convert your normal to a standard normal you can actually do tests and such with it. With software this is becoming a non-issue but it was a big issue when such software wasn't freely available.

Thank You very much

[kenasto]

Another advantage that comes to mind is that you can compare values of differently distributed variables.