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Data Literacy With Python

You're reading from   Data Literacy With Python A Comprehensive Guide to Understanding and Analyzing Data with Python

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Product type Paperback
Published in Jul 2024
Publisher Mercury_Learning
ISBN-13 9781836640097
Length 271 pages
Edition 1st Edition
Languages
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Authors (2):
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Mercury Learning and Information Mercury Learning and Information
Author Profile Icon Mercury Learning and Information
Mercury Learning and Information
Oswald Campesato Oswald Campesato
Author Profile Icon Oswald Campesato
Oswald Campesato
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Table of Contents (9) Chapters Close

Preface
1. Chapter 1: Working With Data FREE CHAPTER 2. Chapter 2: Outlier and Anomaly Detection 3. Chapter 3: Cleaning Datasets 4. Chapter 4: Introduction to Statistics 5. Chapter 5: Matplotlib and Seaborn 6. Index
Appendix A: Introduction to Python 1. Appendix B: Introduction to Pandas

RANDOM VARIABLES

A random variable is a variable that can have multiple values, and where each value has an associated probability of occurrence. For example, if X is a random variable whose values are the outcomes of tossing a well-balanced die, then the values of X are the numbers in the set {1,2,3,4,5,6}. Moreover, each of those values can occur with equal probability (which is 1/6).

In the case of two well-balanced dice, let X be a random variable whose values can be any of the numbers in the set {2,3,4, . . . , 12}. The set of associated probabilities for the different values for X are listed here:

{1/36,2/36,3/36,4/36,5/36,6/36,5/36,4/36,3/26,2/36,1/36}

Discrete Versus Continuous Random Variables

The preceding section contains examples of discrete random variables because the list of possible values is either finite or countably infinite (such as the set of integers). As an aside, the set of rational numbers is also countably infinite, but the set of irrational numbers and also...

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