Z Score
$Z = \frac{X - \mu}{\sigma}$
Explanation: A z-score (also called a standard score) is a raw score that has been transformed into standard deviation units. It tells us how many standard deviations a data point is away from the mean.
Components of the formula:
- Z = Z-score (standardized score)
- X = Raw score (individual data point)
- μ = Mean of the dataset
- σ = Standard deviation of the dataset
Interpretation:- A positive z-score (𝑍>0) means the data point is above the mean.
- A negative z-score (𝑍<0) means the data point is below the mean.
- A z-score of 0 means the data point is exactly at the mean.
Z-scores are useful in comparing data points from different distributions and in probability calculations using the standard normal distribution.