The z-score tells you how many standard deviations a data point is above or below the mean. A positive z-score means the data point is greater than the mean, while a negative z-score means that it is less than the mean. A z-score of 1 means that the data point is exactly 1 standard deviation above the mean.

The easiest way to find the p-value from the z-score is to use a z-score table. The actual calculation involves integrating the area under the curve of a normal distribution.

A z-score table helps you find the p-value, or percentile, your data point corresponds to based on its z-score. Follow these steps:

1. Determine if your z-score is negative or positive.
2. If the z-score is negative (i.e., the data point is less than the mean), use a negative z-score table. If the z-score is positive (i.e., the data point is greater than the mean), use a positive z-score table.
3. Look in the leftmost column to find the z-score that matches yours up to the first decimal (10th place). E.g., for a z-score of 2.15, find 2.1.
4. Look in the top row to find the z-score which matches the second decimal (100th place). E.g., for a z-score of 2.15, find 0.05.
5. Find the p-value where the matching row and column intersect. For a z-score of 2.15, the z-score table gives you a p-value of 0.98422.
6. To find the percentile, multiply the p-value by 100%. A z-score of 2.15 is in the 98th percentile.