# Data Science Statistics Tutorial 003: Normal Distribution and Z-Scores

In this video I step through the normal distribution, which is the most important and popular distribution in statistics.

The normal distribution is used for modeling continuous data as opposed to discrete data. It has some nice properties, such as being symmetric and have equal mean, median, and mode. It is defined by two parameters: the mean, and the variance (or standard deviation). Additionally there is the Empirical Rule which states that:

* 68% of observations will fall within one standard deviation of the mean.
* 95% of observations will fall within two standard deviations of the mean.
* 99.7% of observations will fall within three standard deviations of the mean.

Associated with the normal distribution are z-scores, which are standardized scores telling us the number of standard deviations a measurement is away from the mean.

You need a Normal Probability table to do calculations using z-scores. There are plenty of examples out there, but here is one example: https://cnx.org/contents/[email protected]2/Using-the-Normal-Distribution