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Independent and Identically Distributed
A collection of random variables is independent and identically distributed if each variable has the same probability distribution as the others and all are independent.
Read more at Towards Data Science | Find similar documentsIntuition for Independent and Identically Distributed
The main purpose of data science generally, and machine learning specifically, is to use the past to predict the future. Beyond the specific assumptions of various statistical models, the inescapable…...
Read more at Towards Data Science | Find similar documentsDifferent Probability Distributions Part 2
Now we will see the Continuous variable distributions whereas in part 1 we saw the discrete distributions. In continuous distributions the point probability is equal to “0” and some of the…
Read more at Towards AI | Find similar documentsUncorrelatedness and Independence
A lot of people have difficulties to differentiate principal component analysis (PCA) and independent component analysis (ICA). PCA is a machine learning algorithm that can transform a data set…
Read more at Analytics Vidhya | Find similar documentsRandom Variables and Probability Distributions
Master the random variables and probability distributions and crack your next Data Science Interview with the third part of our Statistics Cheat Sheet series Photo by Naser Tamimi on Unsplash Random ...
Read more at Towards Data Science | Find similar documentsIndependence, Covariance and Correlation between two Random Variables
In this article, I’ll talk about independence, covariance, and correlation between two random variables.
Read more at Towards Data Science | Find similar documentsDistribution of a single variable
It is customary to refer to the raw numbers as data and the output of data analysis as information. You start with the data, and you hope to end with information that an organization can use for…
Read more at Analytics Vidhya | Find similar documentsProbability Distribution
I’m a data scientist for a mobile application. As a data scientist, you will often draw a random sample from the population to conduct experiments or analyses. With the random sample, you make…
Read more at Towards Data Science | Find similar documentsConditional Independence
The independence that can be realized in the real world When it comes to probability theory we all would have heard of joint distribution, marginal distribution, independence, etc. In this article, I...
Read more at Towards AI | Find similar documentsUncorrelated vs Independent Random Variables— Definitions, Proofs, & Examples
Regarding technical knowledge, I’m generally a proponent of having grounded understanding in the methods one is using. I don’t typically like memorizing anything and avoid doing so whenever possible…
Read more at Towards Data Science | Find similar documentsStatistical independence for beginners
Intuitive interpretations with R and Excel functions Continue reading on Towards Data Science
Read more at Towards Data Science | Find similar documentsRandom Variable
One of the basic concepts of statistic is a Random Variable. So, what is Random Variable? Random variable links the outcome of an event to a number. Let’s take an example. X is variable which takes…
Read more at Analytics Vidhya | Find similar documentsAn Introduction to Random Variables & Probability Distribution
Random Variables: A random variable represents the outcome of statistical experiments on numerical values. Discrete Random variables: A variable that can take only the countable number of values. For…...
Read more at Python in Plain English | Find similar documentsThe Normal Distribution
There’s a reason the Normal Distribution is called “normal”. Its presence can be felt throughout data science and machine learning, as well as in a variety of unexpected real-world scenarios. From…
Read more at Towards Data Science | Find similar documentsRandom Variables
In Section 2.6 we saw the basics of how to work with discrete random variables, which in our case refer to those random variables which take either a finite set of possible values, or the integers. In...
Read more at Dive intro Deep Learning Book | Find similar documentsUnderstanding Transformation of Random Variables using Python
A random variable is a numerical description of the outcome of a statistical experiment. It can be discrete or continuous depending upon the outcome of experiment. We would be looking at two kinds of…...
Read more at Analytics Vidhya | Find similar documentsStatistics and probability refresher
From June 2020, I will no longer be using Medium to publish new stories. Please, visit my personal blog if you want to continue to read my articles: https://vallant.in. A foundation in statistics is…
Read more at Towards Data Science | Find similar documentsNormal distribution
The normal distribution is a probability function that defines how the values of a variable are distributed. The normal distribution is a symmetric distribution where most of the observations cluster…...
Read more at Analytics Vidhya | Find similar documentsUnderstanding Random Variables
Random variables are very important in statistics and probability and a must have if any one is looking forward to understand probability distributions. Random Variables many a times confused with…
Read more at Towards Data Science | Find similar documentsStatistical Distributions
The normal distribution is the most important probability distribution in statistics because it fits many natural phenomena. In this article we will cover some distributions that I have found useful…
Read more at Becoming Human: Artificial Intelligence Magazine | Find similar documentsChi-square Test for Independence
Data scientists sometimes need to examine if one categorical variable is related to another one in the same population. If the data is continuous, one can simply calculate the correlation between the…...
Read more at Towards Data Science | Find similar documentsStatistics 101- Part 2- Probability Distributions, Types, and Applications
Definition of the probability distribution, different types of distributions, their explanation, and applications Photo by Naser Tamimi on Unsplash This article is in continuation of Statistics 101-P...
Read more at Towards AI | Find similar documentsProbability Part 1: Probability for Everyone a.s.
Inspired by a course which I am taking in probability theory, this blogpost is an attempt to explain the fundamentals of the mathematical theory of probability at an intuitive level. As the title…
Read more at Towards Data Science | Find similar documentsProperties of the Normal Distribution
The data scientist's guide to the Normal distribution. This article provides an advanced understanding of key concepts using practical experiments coded in Python.
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