**Mean** and **median** are very similar; both determine the mean value of the sample and give us the possibility to conclude the sample of numbers at all.

**Are there any differences between the terms?**

Look at the example of finding **mean** and **median** of the salaries of IT specialists; look at the last of them with the highest salary.

**Conclusion**

The **mean** value is susceptible to extremely small or high values compared to the median. So, if we know that the values in a sequence aren't similar, it is better to use the median. In our example, the mean value is twice higher as the median; the median looks more truly.

Choose lists where the mean and the median value will differ dramatically.

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.

Select a few correct answers