Not a lot. After all, the sample sd is an estimate for the population sd.
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The standardised score decreases.
The standard error increases.
Decrease
1. Compute the square of the difference between each value and the sample mean.2. Add those values up.3. Divide the sum by n-1. This is called the variance.4. Take the square root to obtain the Standard Deviation.Why divide by n-1 rather than n in the third step above?In step 1, you compute the difference between each value and the mean of those values. You don't know the true mean of the population; all you know is the mean of your sample. Except for the rare cases where the sample mean happens to equal the population mean, the data will be closer to the sample mean than it will be to the true population mean.The value you compute in step 2 will probably be a bit smaller (and can't be larger) than what it would be if you used the true population mean in step 1. To make up for this, divide by n-1 rather than n.But why n-1?If you knew the sample mean, and all but one of the values, you could calculate what that last value must be. Statisticians say there are n-1 degrees of freedom.
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