课程: Probability Foundations for Data Science

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Discrete distributions: Introduction

Discrete distributions: Introduction

课程: Probability Foundations for Data Science

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Discrete distributions: Introduction

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- [Presenter] In this chapter, you will explore some popular discrete distributions. Remember, a discrete probability distribution is represented by discrete random variables that contain a finite or countable number of values. You can then gather countable probability values between zero to one that all sum up to equal one. Some discrete distributions you'll review will have extra properties. For example, some discrete distributions, like the binomial distribution, assume the trials conducted in an experiment are independent from each other. Another property is that some distributions, like the geometric distribution, is the memory list property, where the probability of future events depends only on the present state versus the events that occurred prior. The distributions you'll explore in this course include discrete uniform, bernoulli, binomial, negative binomial, geometric, hypergeometric, and poisson. Each video will be structured similarly to give you a general overview of…

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