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Java Data Analysis

You're reading from   Java Data Analysis Data mining, big data analysis, NoSQL, and data visualization

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781787285651
Length 412 pages
Edition 1st Edition
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Author (1):
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John R. Hubbard John R. Hubbard
Author Profile Icon John R. Hubbard
John R. Hubbard
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Table of Contents (14) Chapters Close

Preface 1. Introduction to Data Analysis FREE CHAPTER 2. Data Preprocessing 3. Data Visualization 4. Statistics 5. Relational Databases 6. Regression Analysis 7. Classification Analysis 8. Cluster Analysis 9. Recommender Systems 10. NoSQL Databases 11. Big Data Analysis with Java A. Java Tools Index

Multivariate distributions


A multivariate probability distribution function is one that is induced by several variables. It is also called a joint probability function.

For a simple example, take the two (six-sided) dice experiment again. But this time, suppose that one die is red and the other is green. Let X be the number that comes up on the red die and Y be the number on the green die. These are two random variables, each ranging from 1 to 6. Their probability distribution is a function of those two variables:

For example:

You can see that this probability is 1/36 from the fact that there are 36 possible outcomes and they are all equally likely (assuming the dice are balanced).

For a more interesting example, consider this experiment: a black bag contains two red marbles and four green marbles.

Figure 4-9. Bag of marbles

Except for their color, the marbles are identical. Two marbles are drawn at random from the bag, one after the other, without replacement. Let X be the number of red marbles...

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