课程: Probability Foundations for Data Science

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Continuous distributions: Introduction

Continuous distributions: Introduction

课程: Probability Foundations for Data Science

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Continuous distributions: Introduction

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- [Instructor] In this chapter, you will explore some popular continuous distributions. Remember, a continuous probability distribution is represented by continuous random variables that contain any value within a specified range or interval of uncountable values. You can then gather probability values between 0 to 1 that all sum up to equal 1 over the specified range or interval. The distributions you'll explore in this course include uniform, exponential, gamma, Pareto, standard normal, normal, chi-squared, t, and F. Like usual, remember, t is lowercase and F is uppercase. Each video will be structured similarly to give you a general overview of each distribution. Each video will provide you a definition of the distribution, a list of the distribution properties. The probability density function and cumulative distribution function. The expectation and variance. An example of how to use the distribution to obtain the expectation, variance, PDF, and CDF. And finally, a list of a few…

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