Book description
Master Data Analytics HandsOn 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 bestsellers like Freakonomics and Malcolm
Gladwell’s Outliers: It teaches through a powerful
narrative packed with unforgettable stories.
Murtaza Haider offers informative, jargonfree coverage of basic
theory and technique, backed with plenty of vivid examples and
handson 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.
Table of contents
 About This EBook
 Title Page
 Copyright Page
 Praise for Getting Started with Data Science
 Dedication Page
 ContentsataGlance
 Contents
 Preface
 Acknowledgments
 About the Author
 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
 Random Numbers and Probability Distributions
 Casino Royale: Roll the Dice
 Normal Distribution
 The Student Who Taught Everyone Else
 Statistical Distributions in Action
 Hypothetically Yours
 The Mean and Kind Differences
 WorkedOut Examples of Hypothesis Testing
 Exercises for Comparison of Means
 Regression for Hypothesis Testing
 Analysis of Variance
 Significantly Correlated
 Summary
 Endnotes
 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
 Introducing Time Series Data and How to Visualize It
 How Is Time Series Data Different?
 Starting with Basic Regression Models
 What Is Wrong with Using OLS Models for Time Series Data?
 Time Series Econometrics
 Econometric Models for Time Series Data
 Applying Time Series Tools to Housing Construction
 Estimating Time Series Models to Forecast New Housing Construction
 Summary
 Endnotes

Chapter 12. Data Mining for Gold
 Can Cheating on Your Spouse Kill You?
 Data Mining: An Introduction
 Seven Steps Down the Data Mine

Rattle Your Data
 What Does Religiosity Have to Do with Extramarital Affairs?
 The Principal Components of an Extramarital Affair
 Will It Rain Tomorrow? Using PCA For Weather Forecasting
 Do Men Have More Affairs Than Females?
 Two Kinds of People: Those Who Have Affairs, and Those Who Don’t
 Models to Mine Data with Rattle
 Summary
 Endnotes
 Index
 Code Snippets
Product information
 Title: Getting Started with Data Science: Making Sense of Data with Analytics
 Author(s):
 Release date: December 2015
 Publisher(s): IBM Press
 ISBN: 9780133991246
You might also like
book
Predictive Analytics: Data Mining, Machine Learning and Data Science for Practitioners, 2nd Edition
Use Predictive Analytics to Uncover Hidden Patterns and Correlations and Improve DecisionMaking Using predictive analytics techniques, …
book
Essentials of Data Science and Analytics
Data science and analytics have emerged as the most desired fields in driving business decisions. Using …
book
Machine Learning and Data Science Blueprints for Finance
Over the next few decades, machine learning and data science will transform the finance industry. With …
book
Build a Career in Data Science
You are going to need more than technical knowledge to succeed as a data scientist. Build …