If a z-score is less than 0, then it means that the test value is less than mean.

We can interpret the z-score in the following ways: The formula for calculating a z-score is given below: To determine the greater than values, we need to subtract the less than value from the z-table and then subtract it from 1. Remember that the z-table only tells the less than values. The bell curve of normal distribution is given below: After we have standardized the curve, we use a Z table to find the percentages under the curve. Hence, to facilitate the analysis of the data, we standardize the normal curve in such a way that the mean of the data set is zero and its standard deviation is one. These ranges of the data sets are extremely wide which makes it difficult for a person to analyze the data set. For instance, the ages of the people might range from 15 to 85 and the weight may range from 5 pounds to 350 pounds. We come across data that contains a different set of values.