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
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discover the key concepts covered in this coursedescribe normal distributions and their characteristicsuse the cumulative distribution function (CDF) of a normal distribution and recognize how the mean and standard deviation (SD) influence itvisualize the cumulative distribution function (CDF) for different standard deviations
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recall the symmetrical features of normal distributionsexplain the law of large numbers programmaticallyrecall the central limit theorem and recognize its applicationssummarize the key concepts covered in this course
IN THIS COURSE
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1.Course Overview1m 43sUP NEXT
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2.Working with Normal Distributions9m 48s
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3.Exploring Mean and SD of Normal Distributions10m 6s
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4.Computing the CDF for Various Normal Distributions8m 47s
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5.Analyzing the Symmetry of Normal Distributions9m 35s
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6.Understanding the Law of Large Numbers10m 15s
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7.Exploring the Central Limit Theorem12m 8s
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8.Course Summary1m 42s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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