# Statistics for Big Data For Dummies

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## Overview

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.

Statistics for Big Data For Dummies Cheat Sheet

Summary statistical measures represent the key properties of a sample or population as a single numerical value. This has the advantage of providing important information in a very compact form. It also simplifies comparing multiple samples or populations. Summary statistical measures can be divided into three types: measures of central tendency, measures of central dispersion, and measures of association.