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About the Z-value / Z-statistics

When do we use (x - u / o) and (x - u / SE) to calculate z value?

Thanks.

Yeah I know both are able to arrive at a same conclusion but in a different way (with different methods and answers too). Just clarifying, thanks.

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revenant, both of your points above mean the same thing.

It is like saying, I have $50 and you have $125. And the question is: Do you have more than 3 times as much money than me?

One way is to multiply 50 by 3 to get 150 and compare your 125 with 150 and produce an answer.

Another way is to devide your 125 by my 50 and compare that with 3 and produce the answer.

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revenant Wrote:
-------------------------------------------------------
> I realise (x - u / o) is the z value while (x - u
> / SE) is the z-stats.
>
> Schweser's professor said on page 246 that both
> are the same? Or I misunderstand it?


(x - u)/SD is used for the Distribution of Population. That is, you have your Population Mean and you are comparing another value with the Mean to see how far (how many standard deviations) that value lies away from the Mean.

(x-u)/SE is used for Distribution of Sample Means. Here you are checking how far (how many SEs away) is your Sample Mean away from the Population Mean.

They are basically same things, just the underlying Distribution is different.

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I realised there are 3 ways to tackle hypothesis questions.

1) Using x +- critical value X (u / root n) and compare the final value against u. (e.g. Schweser page 298)

2) Using Z/T Statistics (x - u / SE) and compare the final value against critical value.

3) Using p-value.

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StD would only equal SE when n=1 then.

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What's "o" ?

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The first equation is calculating your standard deviation for your normal distribution. Second, if for hypothesis testing.

But I believe both are the same.

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I realise (x - u / o) is the z value while (x - u / SE) is the z-stats.

Schweser's professor said on page 246 that both are the same? Or I misunderstand it?

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