Statistics for Big Data For Dummies - Alan Anderson

Blick ins Buch

Statistics for Big Data For Dummies (eBook)

Alan Anderson (Autor)

eBook Download: EPUB

2015 | 1. Auflage
384 Seiten
Wiley (Verlag)
978-1-118-94002-0 (ISBN)

Lese- und Medienproben

Ebook-Leseprobe (EPUB)

The fast and easy way to make sense of statistics for big data Does the subject of data analysis make you dizzy? You've come to the right place! Statistics For Big Data For Dummies breaks this often-overwhelming subject down into easily digestible parts, offering new and aspiring data analysts the foundation they need to be successful in the field. Inside, you'll find an easy-to-follow introduction to exploratory data analysis, the lowdown on collecting, cleaning, and organizing data, everything you need to know about interpreting data using common software and programming languages, plain-English explanations of how to make sense of data in the real world, and much more. Data has never been easier to come by, and the tools students and professionals need to enter the world of big data are based on applied statistics. While the word "e;statistics"e; alone can evoke feelings of anxiety in even the most confident student or professional, it doesn't have to. Written in the familiar and friendly tone that has defined the For Dummies brand for more than twenty years, Statistics For Big Data For Dummies takes the intimidation out of the subject, offering clear explanations and tons of step-by-step instruction to help you make sense of data mining without losing your cool. Helps you to identify valid, useful, and understandable patterns in data Provides guidance on extracting previously unknown information from large databases Shows you how to discover patterns available in big data Gives you access to the latest tools and techniques for working in big data If you're a student enrolled in a related Applied Statistics course or a professional looking to expand your skillset, Statistics For Big Data For Dummies gives you access to everything you need to succeed.

Alan Anderson, PhD, is a professor of economics and finance at Fordham University and New York University. He's a veteran economist, risk manager, and fixed income analyst. David Semmelroth is an experienced data analyst, trainer, and statistics instructor who consults on customer databases and database marketing.

Introduction 1

Part I: Introducing Big Data Statistics 7

Chapter 1: What Is Big Data and What Do You Do With It? 9

Chapter 2: Characteristics of Big Data: The Three Vs 19

Chapter 3: Using Big Data: The Hot Applications 27

Chapter 4: Understanding Probabilities 41

Chapter 5: Basic Statistical Ideas 57

Part II: Preparing and Cleaning Data 81

Chapter 6: Dirty Work: Preparing Your Data for Analysis 83

Chapter 7: Figuring the Format: Important Computer File Formats 99

Chapter 8: Checking Assumptions: Testing for Normality 107

Chapter 9: Dealing with Missing or Incomplete Data 119

Chapter 10: Sending Out a Posse: Searching for Outliers 129

Part III: Exploratory Data Analysis (EDA) 141

Chapter 11: An Overview of Exploratory Data Analysis (EDA) 143

Chapter 12: A Plot to Get Graphical: Graphical Techniques 155

Chapter 13: You're the Only Variable for Me: Univariate Statistical Techniques 173

Chapter 14: To All the Variables We've Encountered: Multivariate Statistical Techniques 191

Chapter 15: Regression Analysis 215

Chapter 16: When You've Got the Time: Time Series Analysis 243

Part IV: Big Data Applications 269

Chapter 17: Using Your Crystal Ball: Forecasting with Big Data 271

Chapter 18: Crunching Numbers: Performing Statistical Analysis on Your Computer 297

Chapter 19: Seeking Free Sources of Financial Data 319

Part V: The Part of Tens 331

Chapter 20: Ten (or So) Best Practices in Data Preparation 333

Chapter 21: Ten (or So) Questions Answered by Exploratory Data Analysis (EDA) 339

Index 349

Erscheint lt. Verlag	11.8.2015
Co-Autor	David Semmelroth
Sprache	englisch
Themenwelt	Informatik ► Datenbanken ► Data Warehouse / Data Mining
	Mathematik / Informatik ► Mathematik ► Statistik
	Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
	Technik
Schlagworte	Big Data • Data Mining • Data Mining Statistics • Statistics • Statistik
ISBN-10	1-118-94002-4 / 1118940024
ISBN-13	978-1-118-94002-0 / 9781118940020

Haben Sie eine Frage zum Produkt?

EPUB (Adobe DRM)
Größe: 6,5 MB

Kopierschutz: Adobe-DRM
Adobe-DRM ist ein Kopierschutz, der das eBook vor Mißbrauch schützen soll. Dabei wird das eBook bereits beim Download auf Ihre persönliche Adobe-ID autorisiert. Lesen können Sie das eBook dann nur auf den Geräten, welche ebenfalls auf Ihre Adobe-ID registriert sind.
Details zum Adobe-DRM

Dateiformat: EPUB (Electronic Publication)
EPUB ist ein offener Standard für eBooks und eignet sich besonders zur Darstellung von Belletristik und Sachbüchern. Der Fließtext wird dynamisch an die Display- und Schriftgröße angepasst. Auch für mobile Lesegeräte ist EPUB daher gut geeignet.

Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen eine Adobe-ID und die Software Adobe Digital Editions (kostenlos). Von der Benutzung der OverDrive Media Console raten wir Ihnen ab. Erfahrungsgemäß treten hier gehäuft Probleme mit dem Adobe DRM auf.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen eine Adobe-ID sowie eine kostenlose App.
Geräteliste und zusätzliche Hinweise

Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.