# Probability Distributions: Understanding Normal Distributions

Python 3.7    |    Intermediate
• 8 Videos | 1h 4m 2s
• Includes Assessment
• Earns a Badge
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This course dives deep into normal distributions, also known as Gaussian distributions, while also introducing you to the law of large numbers and the Central Limit Theorem. You will begin by using Python's SciPy library to generate a normal distribution and examine the use of several available functions that allow you to make estimations on normally distributed data. This course will also help you understand and visualize the law of large numbers and explore the Central Limit theorem by generating multiple samples and analyzing them. After you are done with this course, you'll have the skills and knowledge to analyze data and build your own models.

## WHAT YOU WILL LEARN

• discover the key concepts covered in this course
describe normal distributions and their characteristics
use the cumulative distribution function (CDF) of a normal distribution and recognize how the mean and standard deviation (SD) influence it
visualize the cumulative distribution function (CDF) for different standard deviations
• recall the symmetrical features of normal distributions
explain the law of large numbers programmatically
recall the central limit theorem and recognize its applications
summarize the key concepts covered in this course

## IN THIS COURSE

• 1.
Course Overview
• 2.
Working with Normal Distributions
• 3.
Exploring Mean and SD of Normal Distributions
• 4.
Computing the CDF for Various Normal Distributions
• 5.
Analyzing the Symmetry of Normal Distributions
• 6.
Understanding the Law of Large Numbers
• 7.
Exploring the Central Limit Theorem
• 8.
Course Summary

## EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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