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CompTIA Data+: DAO-001 Certification Guide

You're reading from   CompTIA Data+: DAO-001 Certification Guide Complete coverage of the new CompTIA Data+ (DAO-001) exam to help you pass on the first attempt

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Product type Paperback
Published in Dec 2022
Publisher Packt
ISBN-13 9781804616086
Length 370 pages
Edition 1st Edition
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Author (1):
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Cameron Dodd Cameron Dodd
Author Profile Icon Cameron Dodd
Cameron Dodd
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Table of Contents (24) Chapters Close

Preface 1. Part 1: Preparing Data
2. Chapter 1: Introduction to CompTIA Data+ FREE CHAPTER 3. Chapter 2: Data Structures, Types, and Formats 4. Chapter 3: Collecting Data 5. Chapter 4: Cleaning and Processing Data 6. Chapter 5: Data Wrangling and Manipulation 7. Part 2: Analyzing Data
8. Chapter 6: Types of Analytics 9. Chapter 7: Measures of Central Tendency and Dispersion 10. Chapter 8: Common Techniques in Descriptive Statistics 11. Chapter 9: Hypothesis Testing 12. Chapter 10: Introduction to Inferential Statistics 13. Part 3: Reporting Data
14. Chapter 11: Types of Reports 15. Chapter 12: Reporting Process 16. Chapter 13: Common Visualizations 17. Chapter 14: Data Governance 18. Chapter 15: Data Quality and Management 19. Part 4: Mock Exams
20. Chapter 16: Practice Exam One 21. Chapter 17: Practice Exam Two 22. Index 23. Other Books You May Enjoy

Discovering distributions

Distributions are often discussed when statistics come up; they have even been mentioned earlier in this book. The question is, what are they? A statistics class will tell you something like the following: a distribution is a function that describes a line that depicts the probabilities of any theoretical outcome that occurs, based on the evidence of a study. Is this easily understood and actionable information? Not really.

Effectively, you can think of a distribution as a model of historical data. It tells you how likely a specific value is when compared to everything you have collected before. This has all kinds of uses. You can predict the probability that a new entry will be a specific value, or in a range of values. You can take a value and see how it compares to the rest of your information. It even turns out that the shape of your distribution can tell you all kinds of things. Additionally, several statistical methods require a specific distribution...

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