In a normal distribution, what Z-score corresponds to 95% of the data?

To find the Z-score that corresponds to 95% of the data in a normal distribution, it’s essential to know that the normal distribution is symmetric around the mean. When we refer to 95% of the data, we mean that we are looking at the range that covers from the lower tail up to a certain point in the distribution.

In the context of a standard normal distribution, the Z-score represents how many standard deviations a data point is from the mean. For a Z-score that captures the central 95% of the data, we actually are interested in the Z-score that leaves 2.5% in each tail (since 100% minus 95% equals 5%, and half of that 5% is in each tail).

The Z-score associated with the upper 2.5% of the data is critical here. According to standard normal distribution tables or Z-score calculators, this Z-score is approximately 1.96. However, since it is common in practice to round figures, many people may say that the Z-score that corresponds closely to capturing approximately 95% of the central data is often cited as 2.00 for simplicity in various applications, particularly in discussions around confidence intervals and hypothesis testing.

Thus