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