Master Special Probability Distributions in Statistics
.MP4 | Video: 1280x720, 30 fps(r) | Audio: AAC, 44100 Hz, 2ch | 4.52 GB
Duration: 11 hours | Genre: eLearning Video | Language: English
Learn everything about Normal, Binomial, Poisson, Exponential and many more Probability Distributions in this course.
What you'll learn
Binomial Distribution
Poisson Distribution
Geometric Distribution
Hypergeometric Distribution
Uniform or Rectangular Distribution
Exponential or Negative Exponential Distribution
Erlang or General Gamma Distribution
Weibull Distribution
Normal or Gaussian Distribution
Requirements
Knowledge of Applied Probability
Knowledge of Random Variable and Probability Distribution
Knowledge of Statistical Averages
Knowledge of Calculus
Description
As it turns out, there are some specific distributions that are used over and over in practice for e.g. Normal Distribution, Binomial Distribution, Poisson Distribution, Exponential Distribution etc.
There is a random experiment behind each of these distributions. Since these random experiments model a lot of real life phenomenon, these special distribution are used in different applications like Machine Learning, Neural Network, Data Science etc.
That is why they have been given a special names and we devote a course "Master Special Probability Distributions in Statistics" to study them.
This 80+ lecture course includes video explanations of everything from Special Probability Distributions, and it includes more than 45+ examples (with detailed solutions) to help you test your understanding along the way. "Master Special Probability Distributions in Statistics" is organized into the following sections:
Introduction
Binomial Distribution
Poisson Distribution
Geometric Distribution
Hypergeometric Distribution
Uniform or Rectangular Distribution
Exponential or Negative Exponential Distribution
Erlang or General Gamma Distribution
Weibull Distribution
Normal or Gaussian Distribution
Who this course is for:
Current Probability and Statistics students
Students of Machine Learning, Data Science, Computer Science, Electrical Engineering , as Statistics is the prerequisite course to Machine Learning, Data Science, Computer Science and Electrical Engineering
Anyone who wants to study Statistics and its Special Probability Distribution for fun after being away from school for a while.
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