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Hands-On Data Analysis with Scala

You're reading from   Hands-On Data Analysis with Scala Perform data collection, processing, manipulation, and visualization with Scala

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Product type Paperback
Published in May 2019
Publisher Packt
ISBN-13 9781789346114
Length 298 pages
Edition 1st Edition
Languages
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Author (1):
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Rajesh Gupta Rajesh Gupta
Author Profile Icon Rajesh Gupta
Rajesh Gupta
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Toc

Table of Contents (14) Chapters Close

Preface 1. Section 1: Scala and Data Analysis Life Cycle FREE CHAPTER
2. Scala Overview 3. Data Analysis Life Cycle 4. Data Ingestion 5. Data Exploration and Visualization 6. Applying Statistics and Hypothesis Testing 7. Section 2: Advanced Data Analysis and Machine Learning
8. Introduction to Spark for Distributed Data Analysis 9. Traditional Machine Learning for Data Analysis 10. Section 3: Real-Time Data Analysis and Scalability
11. Near Real-Time Data Analysis Using Streaming 12. Working with Data at Scale 13. Another Book You May Enjoy

Hypothesis testing

Hypothesis testing is a statistical tool that is used for the following purposes:

  • Determining whether a result or model is statistically significant or not
  • Ensuring that a result or model did not occur by chance

A statistical hypothesis is used to establish a relationship between data using a sample set of observations. We can call this relationship a result or a model. The goal of hypothesis testing is to eliminate cases where a result occurs by chance. A null hypothesis, on the other hand, establishes that the relationship is not statistically significant.

We typically start with a sample set of observations that consists of values associated with more than one variable. In the Basics of statistics section, we looked at properties of a single variable in isolation, except for Pearson's correlation methodology, where we measured the linear relationship...

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