If a random variable (RV) X is distributed Normally with mean m and standard deviation sthen
Z = (X - m)/s is the corresponding Normal variable which is distributed with mean 0 and variance 1. The distribution of X is difficult to compute but that for Z is readily available. It can be used to find the probabilities of the RV lying in different domains and thereby for testing hypotheses.
A z-score of 0 means the value is the mean.
Z=²8² = 8x8 = 64the value of z = 8
4
The Z Value, or Z Score, does not apply to the mean, it is a representation of a piece of data. z = (x-µ)/sigma
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.
If: z -31 = 64 then the value of z is 95
A z-score of 0 means the value is the mean.
z-score of a value=(that value minus the mean)/(standard deviation). So if a value has a negative z-score, then it is below the mean.
0.97
10.2
The z-score, for a value z, is the probability that a Standard Normal random variable will have a value greater than z.
z-score of a value=(that value minus the mean)/(standard deviation)
z-score of a value=(that value minus the mean)/(standard deviation)
z-score of a value=(that value minus the mean)/(standard deviation)
Z=²8² = 8x8 = 64the value of z = 8
Negative z value means that the raw dat is below the mean, if z value is positive it means that the raw data is above the mean.
z = ±0.44