**Variance**

**Variance** measures how far numbers are spread from the mean.

Look at the distribution of salaries from our dataset:

**Formula**

The formula is different for the sample and population. In this chapter, we will calculate **population variance**.

**Explanation**

The population variance is the sum of the squares of the result of the subtracting population mean from each value of data divided by the number of elements of the population.

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.