A z-score of 0 means the value is the mean.
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For a N(0, 1) distribution, no linear transformation is necessary and so the z-score is the value of the coordinate on the horizontal axis.For a N(0, 1) distribution, no linear transformation is necessary and so the z-score is the value of the coordinate on the horizontal axis.For a N(0, 1) distribution, no linear transformation is necessary and so the z-score is the value of the coordinate on the horizontal axis.For a N(0, 1) distribution, no linear transformation is necessary and so the z-score is the value of the coordinate on the horizontal axis.
IQ is distributed normally, with a mean of 100 and a standard deviation of 15. The z-score of 100 is therefore:(value-mean)*standard deviation= (100-100)*15= 0More generally, a raw score that is equivalent to the mean of a normal distribution will always have a z-score of 0.
z-score of a value=(that value minus the mean)/(standard deviation). So a z-score of -1.5 means that a value is 1.5 standard deviations below the mean.
The z-score must be 1.87: the probability cannot have that value!
p (z<0)