Probability Distributions: Understanding Normal Distributions

Python    |    Intermediate
  • 8 videos | 1h 4m 2s
  • Includes Assessment
  • Earns a Badge
Rating 4.8 of 4 users Rating 4.8 of 4 users (4)
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
  • Locked
    3.  Exploring Mean and SD of Normal Distributions
    10m 6s
  • Locked
    4.  Computing the CDF for Various Normal Distributions
    8m 47s
  • Locked
    5.  Analyzing the Symmetry of Normal Distributions
    9m 35s
  • Locked
    6.  Understanding the Law of Large Numbers
    10m 15s
  • Locked
    7.  Exploring the Central Limit Theorem
    12m 8s
  • Locked
    8.  Course Summary
    1m 42s

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