Summary
The chapter explains discrete versus continuous data types: discrete variables hold whole‐number counts while continuous variables can assume any real value within a range.

General domain of usage
Statistical data analysis

With the basics covered, it's time to explore the different data categories used in statistics and how they guide analysis.

Now consider a sample of people described by two variables:
- Number of teeth;
- Height.

The **number of teeth** is considered a discrete variable because teeth are counted in **whole numbers**, and you cannot have a fractional or decimal part of a tooth. Each individual has a specific, **countable** number of teeth, and the count is a distinct and separate value.

In contrast, **height** is considered a continuous variable because it can take on **any** value within a certain range, and there is an **infinite** number of  values in the interval between any two values of heights.

Learn core statistical concepts used in data analysis with Python. The course covers descriptive statistics, including mean, median, mode, variance, and standard deviation, as well as sampling, probability distributions, the Central Limit Theorem, and outlier detection.

Types of Data