In the same way that you would convert a positive z-score. Only leave a negative sign in front of it.
The sign of the z score is negative if the observation was below the mean and positive if it was greater.
Yes.z = (raw score - mean)/standard error.Since the standard error is positive, z < 0 => (raw score - mean) < 0 => raw score < mean.
interpret it by letters...........
In general, the answer is no, both negative and positive z score values should be expected. A z-score (or standardize score) is the raw data value minus the mean and then this result divided by the standard deviation. If the data can be considered normally distributed and a random sample is taken from a population, then as the sample size becomes large, approximately half the z-scores should be negative and half of the z-scores should be positive. There are some exceptions. Small data sets may have only positive values. A non-normal (skewed) distribution if skewed to the right, may have, after normalizing, may have a higher portion of z scores as positives.
A negative z score is a value that is less than the mean value.
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.
Yes. If a score is below the mean, the z score will be negative.
no, z score can be negative but a probability is a always positive between 0 and 1.
Let z be positive so that -z is the negative z score for which you want the probability. Pr(Z < -z) = Pr(Z > z) = 1 - Pr(Z < z).
In the same way that you would convert a positive z-score. Only leave a negative sign in front of it.
The sign of the z score is negative if the observation was below the mean and positive if it was greater.
A z score of -1.3 means that the score is located at the negative 1.3 sigma level with respect to the mean.
Assume the z-score is relative to zero score. In simple terms, assume that we have 0 < z < z0, where z0 is the arbitrary value. Then, a negative z-score can be greater than a positive z-score (yes). How? Determine the probability of P(-2 < z < 0) and P(0 < z < 1). Then, by checking the z-value table, you should get: P(-2 < z < 0) ≈ 0.47725 P(0 < z < 1) ≈ 0.341345
The z score is -2 or +2!
A negative Z-Score corresponds to a negative standard deviation, i.e. an observation that is less than the mean, when the standard deviation is normalized so that the standard deviation is zero when the mean is zero.
It means that it is less than the mean.