Book description
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 "statistics" 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.
Table of contents
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- Cover
- Introduction
- Part I: Introducing Big Data Statistics
- Part II: Preparing and Cleaning Data
-
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
- The Fundamental Assumption: Variables Have a Linear Relationship
- Defining the Population Regression Equation
- Estimating the Population Regression Equation
- Testing the Estimated Regression Equation
- Using Statistical Software
- Assumptions of Simple Linear Regression
- Multiple Regression Analysis
- Multicollinearity
- Chapter 16: When You’ve Got the Time: Time Series Analysis
- Part IV: Big Data Applications
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Part V: The Part of Tens
- Chapter 20: Ten (or So) Best Practices in Data Preparation
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Chapter 21: Ten (or So) Questions Answered by Exploratory Data Analysis (EDA)
- What Are the Key Properties of a Dataset?
- What’s the Center of the Data?
- How Much Spread Is There in the Data?
- Is the Data Skewed?
- What Distribution Does the Data Follow?
- Are the Elements in the Dataset Uncorrelated?
- Does the Center of the Dataset Change Over Time?
- Does the Spread of the Dataset Change Over Time?
- Are There Outliers in the Data?
- Does the Data Conform to Our Assumptions?
- About the Authors
- Cheat Sheet
- Advertisement Page
- Connect with Dummies
- End User License Agreement
Product information
- Title: Statistics for Big Data For Dummies
- Author(s):
- Release date: September 2015
- Publisher(s): For Dummies
- ISBN: 9781118940013
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