Formula for z Score….
The z-score formula is used to standardize a given value by calculating how many standard deviations it is away from the mean of a distribution
The z-score formula is used to standardize a given value by calculating how many standard deviations it is away from the mean of a distribution. It allows us to compare and interpret data points from different normal distributions.
The formula for calculating the z-score is:
z = (x – μ) / σ
Where:
– z is the z-score
– x is the given value
– μ is the mean of the distribution
– σ is the standard deviation of the distribution
To find the z-score, subtract the mean from the given value (x – μ), and then divide the result by the standard deviation (σ). This equation quantifies how many standard deviations away the value is from the mean.
The z-score provides valuable information about the relative position of a data point within a distribution. A positive z-score indicates that the data point is above the mean, while a negative z-score indicates that it is below the mean. Furthermore, the magnitude of the z-score informs us about the distance from the mean in terms of standard deviations.
By using the z-score, we can compare values from different normal distributions and determine how unusual or typical a specific data point is in relation to the rest of the data.
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