PurdueX: Probability: Distribution Models & Continuous Random Variables
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Learn about probability distribution models, including normal distribution, and continuous random variables to prepare for a career in information and data science.
About this course
In this statistics and data analysis course, you will learn about continuous random variables and some of the most frequently used probability distribution models including, exponential distribution, Gamma distribution, Beta distribution, and most importantly, normal distribution.
You will learn how these distributions can be connected with the Normal distribution by Central limit theorem (CLT). We will discuss Markov and Chebyshev inequalities, order statistics, moment generating functions and transformation of random variables.
This course along with the recommended pre-requisite,Probability: Basic Concepts & Discrete Random Variables,will you give the skills and knowledge to progress towards an exciting career in information and data science.
The Center for Science of Information, a National Science Foundation Center, supports learners by offering free educational resources in information science.
At a Glance:
Institution: PurdueX
Subject: Computer Science
Level: Intermediate
Prerequisites:
Basic Calculus 1&2, and Calculus 3 (including an understanding of double integers)
Complete this course first: 416.1x Probability: Basic Concepts & Discrete Random Variables
Language: English
Video Transcript: English
Associated skills:Statistics, Random Variables, Data Analysis, Probability, Data Science, Probability Distribution, Normal Distribution
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