Description
Book SynopsisDoes the subject of data analysis make you dizzy? This book features 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. It helps you to identify valid, useful, and understandable patterns in data.
Table of ContentsIntroduction 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
