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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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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

Applying Statistics and Hypothesis Testing

This chapter provides an overview of statistical methods used in data analysis and covers techniques for deriving meaningful insights from data. We will first look at some basic statistical techniques used to gain a better understanding of data before moving on to more advanced methods that are used to compute statistics on vectorized data instead of simple scalar data.

This chapter also covers the various techniques for generating random numbers. Random numbers play a significant part in data analysis because they help us work with sample data in much smaller datasets. A good random sample selection ensures that smaller datasets can act as a good representative of the much bigger dataset.

We will also gain an understanding of hypothesis testing and look at some Scala tools readily available to make this task easier.

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