Understanding Z-Scores

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By subtracting the X-value from the mean and multiplying by the standard deviation.
By averaging the X-value and the mean.
By adding the mean to the X-value and dividing by the standard deviation.
By subtracting the mean from the X-value and dividing by the standard deviation. (correct)

It shows the score's rank within the data set.
It represents the score's absolute difference from the mean.
It expresses the score's distance in terms of the number of standard deviations. (correct)
It indicates the score's percentage difference from the mean.

<p>Z-scores allow for comparison of scores across different data sets. (A)</p> Signup and view all the answers

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Z-scores indicate the precise position of a score within a statistical distribution.
They serve as standardized values, facilitating comparisons between different datasets.
Z-scores are derived by adjusting each X-value into a signed number, either positive (+) for scores above the mean or negative (-) for scores below it.
The absolute value of the Z-score represents the distance from the mean in terms of standard deviations.
Calculation of a Z-score is performed by subtracting the mean from the X-value and dividing the result by the standard deviation.
Z-scores help identify how unusual or typical a score is within a given distribution.