## Learning Statistics with Python

ADVANCED

#python

Author: Polina Sandatsian

Course description

This course gives you a basic knowledge of statistics. It is intended for students with basic knowledge of Python syntax as they will be working with NumPy and pandas modules. During the course, you will become familiar with the basic concepts and then gradually move on to more complex concepts and tasks.

Complete all chapters to get certificate

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Basic Concepts

Sample vs Population

Types of Statistics

Types of Data

Mean Value

Median Value

Median Value of the Even Number of Values

Mean or Median

Mode Value

Challenge

Mean, Median and Mode with Python

Examine Dataset

Calculate Mean and Median Values with Python

Statistics with pandas

Challenge

Variance and Standard Deviation

Population Variance

Sample Variance

Calculate Variance with Python

Standard deviation

Standard Deviation with Python

Challenge

Covariance vs Correlation

Covariance

Correlation

Challenge 1

Challenge 2

Confidence Interval

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!

Explore the Data Set

Confidence Interval

Calculating Confidence Interval with Python

Challenge 1

Challenge 2

Calculating Confidence Interval with Python

Challenge

Statistical Testing

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.

What is t-test

Hypotheses

t-test Mathematically

One-Tailed And Two-Tailed Test

t-test Assumptions

Performing a t-test in Python

Challenge

Paired t-test