OCR S2 Standardising normal distributions Watch

jamie092
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I understand that Z is a normal distribution with Mean 0, and variance 1. You can apparently convert any normally distributed variable into Z by subtracting the mean, and then dividing by the standard deviation.

I understand that if the mean is subtracted, then the bell curve now has mean 0, but I don't quite understand why you then divide by the SD. I know how to do the questions, I just don't understand why I'm using the method that I am.

So yeah if anyone could explain it that would be great =)
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jamie092
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ghostwalker
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(Original post by jamie092)
buuuump
You're basically doing a graph transformation. Starting from a normal distribution. Subtracting the mean is moving it to the left or right; dividing by the s.d. is scaling the x-axis. When you do that you end up with the standardized normal distribution.

If you happen to have cumulative normal distribution tables for your particular normal distribution you don't need to do the transformation. BUT since the normal distribution cannot be easily integrated you'd have to use numerical methods to work out the values each time; bit of a bore. Hence standardize and use the tables provided.
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