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Getting Started with Data Science: Making Sense of Data with Analytics

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Getting Started with Data Science: Making Sense of Data with Analytics

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  • About eBook Formats
  • This eBook includes the following formats, accessible from your Account page after purchase:

    ePub EPUB The open industry format known for its reflowable content and usability on supported mobile devices.

    MOBI MOBI The eBook format compatible with the Amazon Kindle and Amazon Kindle applications.

    Adobe Reader PDF The popular standard, used most often with the free Adobe® Reader® software.

    This eBook requires no passwords or activation to read. We customize your eBook by discreetly watermarking it with your name, making it uniquely yours.

About

Features

  • Teaches data analytics with the same popular approach that made Freakonomics and Malcolm Gladwell's books worldwide best-sellers
  • Covers crucial ingredients for practical success with data analytics -- especially how to create powerful, visual narratives to explain findings and make them actionable
  • Practical, hands-on, and product independent: supports any tool, application, or environment
  • Gives students extensive practice -- not just a single example for each concept
  • By an expert who has crafted 50+ of the world's most popular data analytics instructional videos

Description

  • Copyright 2016
  • Dimensions: 7" x 9-1/8"
  • Pages: 608
  • Edition: 1st
  • Book
  • ISBN-10: 0-13-399102-4
  • ISBN-13: 978-0-13-399102-4

Master Data Analytics Hands-On by Solving Fascinating Problems You’ll Actually Enjoy!

Harvard Business Review recently called data science “The Sexiest Job of the 21st Century.” It’s not just sexy: For millions of managers, analysts, and students who need to solve real business problems, it’s indispensable. Unfortunately, there’s been nothing easy about learning data science–until now.

Getting Started with Data Science takes its inspiration from worldwide best-sellers like Freakonomics and Malcolm Gladwell’s Outliers: It teaches through a powerful narrative packed with unforgettable stories.

Murtaza Haider offers informative, jargon-free coverage of basic theory and technique, backed with plenty of vivid examples and hands-on practice opportunities. Everything’s software and platform agnostic, so you can learn data science whether you work with R, Stata, SPSS, or SAS. Best of all, Haider teaches a crucial skillset most data science books ignore: how to tell powerful stories using graphics and tables. Every chapter is built around real research challenges, so you’ll always know why you’re doing what you’re doing.

You’ll master data science by answering fascinating questions, such as:
• Are religious individuals more or less likely to have extramarital affairs?
• Do attractive professors get better teaching evaluations?
• Does the higher price of cigarettes deter smoking?
• What determines housing prices more: lot size or the number of bedrooms?
• How do teenagers and older people differ in the way they use social media?
• Who is more likely to use online dating services?
• Why do some purchase iPhones and others Blackberry devices?
• Does the presence of children influence a family’s spending on alcohol?

For each problem, you’ll walk through defining your question and the answers you’ll need; exploring how
others have approached similar challenges; selecting your data and methods; generating your statistics;
organizing your report; and telling your story. Throughout, the focus is squarely on what matters most:
transforming data into insights that are clear, accurate, and can be acted upon.

Downloads

Downloads

Download the code files:

Chapter 4 (444 KB .zip)

Chapter 5 (2.37 MB .zip)

Chapter 6 (769 KB .zip)

Chapter 7 (813 KB .zip)

Chapter 8 (909 KB .zip)

Chapter 9 (3.51 MB .zip)

Chapter 10 (1.89 KB .zip)

Chapter 11 (294 KB .zip)

Chapter 12 (43 KB .zip)

Source Code

Download the code files from this book.

Sample Content

Online Sample Chapter

Getting Started with Data Science: Hypothetically Speaking

Sample Pages

Download the sample pages (includes Chapter 6 and Index)

Table of Contents

  • Chapter 1  The Bazaar of Storytellers    
  • Chapter 2  Data in the 24/7 Connected World   
  • Chapter 3  The Deliverable    
  • Chapter 4  Serving Tables   
  • Chapter 5  Graphic Details   
  • Chapter 6  Hypothetically Speaking      
  • Chapter 7  Why Tall Parents Don’t Have Even Taller Children        
  • Chapter 8  To Be or Not to Be    
  • Chapter 9  Categorically Speaking About Categorical Data       
  • Chapter 10  Spatial Data Analytics    
  • Chapter 11  Doing Serious Time with Time Series 
  • Chapter 12  Data Mining for Gold     
  • Index  

Updates

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