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.