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discrete-distributions
Discrete distributions are a fundamental concept in statistics and data science, representing the probability distribution of discrete random variables. These variables take on distinct, separate values, often associated with counts or whole-number outcomes. Common examples include the number of students in a classroom or the number of successful events in a series of trials. Discrete distributions can be categorized into various types, such as the Bernoulli, Binomial, and Poisson distributions, each serving specific applications in probability theory. Understanding these distributions is essential for analyzing data patterns and making informed decisions based on statistical insights.
Data Distributions
In data science, data distributions show how values are spread in a dataset. It helps highlight patterns, measure variability, and reveal the overall shape of the data. Distributions are often grouped...
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The Bernoulli and Binomial Distributions
The probability for a discrete random variable can be summarized with a discrete probability distribution. A discrete random variable is a random variable that can have one of a finite set of…
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An Introduction to Discrete Distribution Function
Binomial Distribution: In probability theory and statistics, the binomial distribution is the discrete probability distribution that gives only two possible results in an experiment, either Success…
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The Discrete ‘Movie Rating’ Distribution
Distributions are pre-defined math functions that describe a real-world pattern (this is not the formal definition, however is a very intuitive understanding of why you would ever study distributions…...
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The 5 discrete distributions every Data Scientist should know
Now coming from a non-statistical background, distributions always come across as something mystical to me. This post is about some of the most used discrete distributions that you need to know along…...
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Discrete Probability Distributions with R
In simpler terms, the probability distributions describe the random process (any phenomenon) in terms of probabilities. A random event is a random process to which we can never find the exact value…
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Discrete Probability Distributions for Machine Learning
Last Updated on October 6, 2020 The probability for a discrete random variable can be summarized with a discrete probability distribution. Discrete probability distributions are used in machine learni...
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Univariate Discrete Distributions: An Easy-to-Understand Explanation
Do you know this feeling? You want to learn something new, but you don’t know where to start. This is how we felt when we wanted to understand distributions mathematically. Yes, our professor explaine...
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Statistical Distributions
A probability distribution is a mathematical function that provides the probabilities of the occurrence of various possible outcomes in an experiment. Probability distributions are used to define…
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Seven Must-Know Statistical Distributions and Their Simulations for Data Science
A statistical distribution is a parameterized mathematical function that gives the probabilities of different outcomes for a random variable. There are discrete and continuous distributions depending…...
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Distributions
Now that we have learned how to work with probability in both the discrete and the continuous setting, let’s get to know some of the common distributions encountered. Depending on the area of machine ...
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7 Types of Discrete Probability Distributions and Their Applications in R
7 types of Discrete Probability Distributions clearly explained in 10 minutes. (With code in R)!
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