Statistics for Big Data For Dummies

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.

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.

Learn to: Collect, clean, and interpret data Effectively communicate data analysis Make good predictions Big data making you dizzy? Relax--here's what it's all about Big data figures into everything from weather forecasting to political polling. Don't let it give you a big headache; use this friendly book to learn about it in manageable, bite-size chunks. You'll get a handle on the statistical methods used when working with big data, applications for it, ways to organize and check data, and a whole lot more. Solving the big mystery --find out what big data is, characteristics that define it, how it's used, and what it makes possible How to handle it -- explore statistical techniques used with big data, including probability distributions, regression analysis, time series analysis, and forecasting techniques Getting graphical -- learn how big data can be analyzed with graphical techniques and how to identify valid, useful, and understandable patterns in data A variable approach -- examine key univariate and multivariate statistical techniques for analyzing data Thinking ahead -- discover techniques for forecasting the future values of a dataset There's a tool for that -- learn about the best software packages and programming tools for analyzing statistical data Open the book and find: Ways to extract previously unknown information from a database Tips for data collection and cleaning Techniques for analyzing time series data How to check data for missing information What to do with outliers in a dataset Some surprising uses for big data An overview of modeling techniques

Learn to: Collect, clean, and interpret data Effectively communicate data analysis Make good predictions Big data making you dizzy? Relax here's what it's all about Big data figures into everything from weather forecasting to political polling. Don't let it give you a big headache; use this friendly book to learn about it in manageable, bite-size chunks. You'll get a handle on the statistical methods used when working with big data, applications for it, ways to organize and check data, and a whole lot more. Solving the big mystery find out what big data is, characteristics that define it, how it's used, and what it makes possible How to handle it explore statistical techniques used with big data, including probability distributions, regression analysis, time series analysis, and forecasting techniques Getting graphical learn how big data can be analyzed with graphical techniques and how to identify valid, useful, and understandable patterns in data A variable approach examine key univariate and multivariate statistical techniques for analyzing data Thinking ahead discover techniques for forecasting the future values of a dataset There's a tool for that learn about the best software packages and programming tools for analyzing statistical data Open the book and find: Ways to extract previously unknown information from a database Tips for data collection and cleaning Techniques for analyzing time series data How to check data for missing information What to do with outliers in a dataset Some surprising uses for big data An overview of modeling techniques

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