Now, we will move to the statistical measurements. The first one is called **mean value**. We can find the **mean** by adding all numbers in the sequence of data and then dividing by the value quantity.

Look at the picture where we will find the **mean** value of people's salaries.

This section will help us deal with the first real statistical case: finding confidence intervals. It requires knowledge of NumPy, pandas, Matplotlib, and Seaborn library to calculate math formulas and build visualization! To encourage you to pass this section, I want to point out that you will run across a small amount of theory but a significant amount of practice!

An inseparable part of a data analyst's life is conducting hypothesis testing. After completing this section, you will understand the idea behind testing in statistics and will be able to conduct a t-test using Python.