Probability Distributions: Understanding Normal Distributions
Python 3.7
| Intermediate
- 8 videos | 1h 4m 2s
- Includes Assessment
- Earns a Badge
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
-
1m 43s
-
9m 48s
-
3. Exploring Mean and SD of Normal Distributions10m 6s
-
4. Computing the CDF for Various Normal Distributions8m 47s
-
5. Analyzing the Symmetry of Normal Distributions9m 35s
-
6. Understanding the Law of Large Numbers10m 15s
-
7. Exploring the Central Limit Theorem12m 8s
-
8. Course Summary1m 42s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
Skillsoft is providing you the opportunity to earn a digital badge upon successful completion on some of our courses, which can be shared on any social network or business platform.
Digital badges are yours to keep, forever.
