Statistics for Big Data for Dummies

Description

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.

About the Author

Alan Andersonis a professor of economics and finance at Fordham University and New York University. He's a veteran economist

Table of Contents

Introduction

Part I: Introducing Big Data Statistics

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

Chapter 2: Characteristics of Big Data: The Three Vs

Chapter 3: Using Big Data: The Hot Applications

Chapter 4: Understanding Probabilities

Chapter 5: Basic Statistical Ideas

Part II: Preparing and Cleaning Data

Chapter 6: Dirty Work: Preparing Your Data for Analysis

Chapter 7: Figuring the Format: Important Computer File Formats

Chapter 8: Checking Assumptions: Testing for Normality

Chapter 9: Dealing with Missing or Incomplete Data

Chapter 10: Sending Out a Posse: Searching for Outliers

Part III: Exploratory Data Analysis (EDA)

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

Chapter 12: A Plot to Get Graphical: Graphical Techniques

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

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

Chapter 15: Regression Analysis

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

Part IV: Big Data Applications

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

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

Chapter 19: Seeking Free Sources of Financial Data

Part V: The Part of Tens

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

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

Index