Since the mean for the standard normal distribution is zero and the standard deviation is one, then the transformation in Equation \ref{zscore} produces the distribution \(Z \sim N(0, 1)\). The value \(x\) comes from a normal distribution with mean \(\mu\) and standard deviation \(\sigma\). A z-score is measured in units of the standard deviation. You’ll use this value in Step 4 to find a z-score. Step 3: Use the continuity correction factor on the X value. For this example, we have a greater than or equals sign (≥), so the table tells us: P(X ≥ n) use P(X > n – 0.5) X ≥ 8 becomes X ≥ 7.5. Step 4: Find the z-score. You’ll need all three values from above: The mean (x̄ U7IY.

can i use z score for non normal distribution