Paul McFedries - Excel Data Analysis For Dummies (For Dummies (Computer/Tech))

Excel Data Analysis For Dummies, 5th Edition

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Published simultaneously in Canada

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ISBN 978-1-119-84442-6 (pbk); ISBN 978-1-119-84446-4 (ebk); ISBN 978-1-119-84447-1 (ebk)

1. Chapter 3
2. Chapter 12

1. Chapter 1
2. Chapter 2
3. Chapter 3
4. Chapter 4
5. Chapter 5
6. Chapter 6
7. Chapter 7
8. Chapter 8
9. Chapter 9
10. Chapter 10
11. Chapter 11
12. Chapter 12
13. Chapter 13
14. Chapter 14
15. Chapter 16

The world is bursting at the seams with data. Its on our computers, its in our networks, its on the web. Some days, it seems to be in the very air itself, borne on the wind. But heres the thing: No one actually cares about data. A collection of data whether it resides on your PC or some giant server somewhere is really just a bunch of numbers and text, dates and times. No one cares about data because data doesnt mean anything. Data isnt cool. You know whats cool? Knowledge is cool. Insight is cool.

So how do you turn data into knowledge? How do you tweak data to generate insight? You need to organize that data, and then you need to sort it, filter it, run calculations on it, and summarize it. In a word, you need to analyze the data.

Now for the good news: If you have (or can get) that data into Excel, you have a giant basket of data-analysis tools at your disposal. Excel really seems to have been made with data analysis in mind, because it offers such a wide variety of features and techniques for organizing, manipulating, and summarizing just about anything that resides in a worksheet. If you can get your data into Excel, it will help you turn that data into knowledge and insight.

This book takes you on a tour of Excels data-analysis tools. You learn everything you need to know to make your data spill its secrets and to uncover your datas hidden-in-plain-sight wisdom. Best of all, if you already know how to perform the basic Excel chores, you dont need to learn any other fancy-schmancy Excel techniques to get started in data analysis. Sweet? You bet.

This book contains 16 chapters (and a bonus appendix), but that doesnt mean that you have to, as the King says gravely in Alices Adventures in Wonderland, Begin at the beginning and go on till you come to the end: Then stop. If youve done a bit of data-analysis work in the past, please feel free to dip into the book wherever it strikes your fancy. The chapters all present their data-analysis info and techniques in readily digestible, bite-sized chunks, so you can certainly graze your way through this book.

However, if youre brand spanking new to data analysis particularly if youre not even sure what data analysis even is no problem: Im here to help. To get your data-analysis education off to a solid start, I highly recommend reading the books first three chapters to get some of the basics down cold. From there, you can travel to more advanced territory, safe in the knowledge that youve got some survival skills to fall back on.

This book consists of several hundred pages. Do I expect you to read every word on every page? Yes, I do. Just kidding! No, of course I dont. Entire sections heck, maybe even entire chapters might contain information thats not relevant to what you do. Thats fine and my feelings wont be hurt if you skim through (or whos kidding whom? skip over) those parts of the book.

If time (or attention) is short, what else might you want to ignore? Okay, in many places throughout the book I provide step-by-step instructions to complete some task. Each of those steps includes some bold type that gives you the basic instruction. In many cases, however, below that bold text I offer supplementary information to flesh out or extend or explain the bold instruction. Am I just showing off how much I know about all this stuff? Yes, sometimes. Do you have to read these extended instructions? Nope. Read the bold stuff, for sure, but feel free to skip the details if they seem unnecessary or unimportant.