How to Use This Book: Intro

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In this section we answer the burning question: “So why DID they put that in a data analysis book?”

Who is this book for?

If you can answer “yes” to all of these:

  1. Do you feel like there’s a world of insights buried in your data that you’d only be able to access if you had the right tools?

  2. Do you want to learn, understand, and remember how to create brilliant graphics, test hypotheses, run a regression, or clean up messy data?

  3. Do you prefer stimulating dinner party conversation to dry, dull, academic lectures?

this book is for you.

Who should probably back away from this book?

If you can answer “yes” to any of these:

  1. Are you a seasoned, brilliant data analyst looking for a survey of bleeding edge data topics?

  2. Have you never loaded and used Microsoft Excel or OpenOffice calc?

  3. Are you afraid to try something different? Would you rather have a root canal than mix stripes with plaid? Do you believe that a technical book can’t be serious if it anthropomorphizes control groups and objective functions?

this book is not for you.

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[Note from marketing: this book is for anyone with a credit card.]

We know what you’re thinking

“How can this be a serious data analysis book?”

“What’s with all the graphics?”

“Can I actually learn it this way?”

We know what your brain is thinking

Your brain craves novelty. It’s always searching, scanning, waiting for something unusual. It was built that way, and it helps you stay alive.

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So what does your brain do with all the routine, ordinary, normal things you encounter? Everything it can to stop them from interfering with the brain’s real job—recording things that matter. It doesn’t bother saving the boring things; they never make it past the “this is obviously not important” filter.

How does your brain know what’s important? Suppose you’re out for a day hike and a tiger jumps in front of you, what happens inside your head and body?

Neurons fire. Emotions crank up. Chemicals surge.

And that’s how your brain knows...

This must be important! Don’t forget it!

But imagine you’re at home, or in a library. It’s a safe, warm, tiger-free zone. You’re studying. Getting ready for an exam. Or trying to learn some tough technical topic your boss thinks will take a week, ten days at the most.

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Just one problem. Your brain’s trying to do you a big favor. It’s trying to make sure that this obviously non-important content doesn’t clutter up scarce resources. Resources that are better spent storing the really big things. Like tigers. Like the danger of fire. Like how you should never have posted those “party” photos on your Facebook page. And there’s no simple way to tell your brain, “Hey brain, thank you very much, but no matter how dull this book is, and how little I’m registering on the emotional Richter scale right now, I really do want you to keep this stuff around.”

Metacognition: thinking about thinking

If you really want to learn, and you want to learn more quickly and more deeply, pay attention to how you pay attention. Think about how you think. Learn how you learn.

Most of us did not take courses on metacognition or learning theory when we were growing up. We were expected to learn, but rarely taught to learn.

But we assume that if you’re holding this book, you really want to learn data analysis. And you probably don’t want to spend a lot of time. If you want to use what you read in this book, you need to remember what you read. And for that, you’ve got to understand it. To get the most from this book, or any book or learning experience, take responsibility for your brain. Your brain on this content.

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The trick is to get your brain to see the new material you’re learning as Really Important. Crucial to your well-being. As important as a tiger. Otherwise, you’re in for a constant battle, with your brain doing its best to keep the new content from sticking.

So just how DO you get your brain to treat data analysis like it was a hungry tiger?

There’s the slow, tedious way, or the faster, more effective way. The slow way is about sheer repetition. You obviously know that you are able to learn and remember even the dullest of topics if you keep pounding the same thing into your brain. With enough repetition, your brain says, “This doesn’t feel important to him, but he keeps looking at the same thing over and over and over, so I suppose it must be.”

The faster way is to do anything that increases brain activity, especially different types of brain activity. The things on the previous page are a big part of the solution, and they’re all things that have been proven to help your brain work in your favor. For example, studies show that putting words within the pictures they describe (as opposed to somewhere else in the page, like a caption or in the body text) causes your brain to try to makes sense of how the words and picture relate, and this causes more neurons to fire. More neurons firing = more chances for your brain to get that this is something worth paying attention to, and possibly recording.

A conversational style helps because people tend to pay more attention when they perceive that they’re in a conversation, since they’re expected to follow along and hold up their end. The amazing thing is, your brain doesn’t necessarily care that the “conversation” is between you and a book! On the other hand, if the writing style is formal and dry, your brain perceives it the same way you experience being lectured to while sitting in a roomful of passive attendees. No need to stay awake.

But pictures and conversational style are just the beginning...

Here’s what WE did

We used pictures, because your brain is tuned for visuals, not text. As far as your brain’s concerned, a picture really is worth a thousand words. And when text and pictures work together, we embedded the text in the pictures because your brain works more effectively when the text is within the thing the text refers to, as opposed to in a caption or buried in the text somewhere.

We used redundancy, saying the same thing in different ways and with different media types, and multiple senses, to increase the chance that the content gets coded into more than one area of your brain.

We used concepts and pictures in unexpected ways because your brain is tuned for novelty, and we used pictures and ideas with at least some emotional content, because your brain is tuned to pay attention to the biochemistry of emotions. That which causes you to feel something is more likely to be remembered, even if that feeling is nothing more than a little humor, surprise, or interest.

We used a personalized, conversational style, because your brain is tuned to pay more attention when it believes you’re in a conversation than if it thinks you’re passively listening to a presentation. Your brain does this even when you’re reading.

We included more than 80 activities, because your brain is tuned to learn and remember more when you do things than when you read about things. And we made the exercises challenging-yet-do-able, because that’s what most people prefer.

We used multiple learning styles, because you might prefer step-by-step procedures, while someone else wants to understand the big picture first, and someone else just wants to see an example. But regardless of your own learning preference, everyone benefits from seeing the same content represented in multiple ways.

We include content for both sides of your brain, because the more of your brain you engage, the more likely you are to learn and remember, and the longer you can stay focused. Since working one side of the brain often means giving the other side a chance to rest, you can be more productive at learning for a longer period of time.

And we included stories and exercises that present more than one point of view, because your brain is tuned to learn more deeply when it’s forced to make evaluations and judgments.

We included challenges, with exercises, and by asking questions that don’t always have a straight answer, because your brain is tuned to learn and remember when it has to work at something. Think about it—you can’t get your body in shape just by watching people at the gym. But we did our best to make sure that when you’re working hard, it’s on the right things. That you’re not spending one extra dendrite processing a hard-to-understand example, or parsing difficult, jargon-laden, or overly terse text.

We used people. In stories, examples, pictures, etc., because, well, because you’re a person. And your brain pays more attention to people than it does to things.

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Here’s what YOU can do to bend your brain into submission

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So, we did our part. The rest is up to you. These tips are a starting point; listen to your brain and figure out what works for you and what doesn’t. Try new things.

Note

Cut this out and stick it on your refrigerator.

  1. Slow down. The more you understand, the less you have to memorize.

    Don’t just read. Stop and think. When the book asks you a question, don’t just skip to the answer. Imagine that someone really is asking the question. The more deeply you force your brain to think, the better chance you have of learning and remembering.

  2. Do the exercises. Write your own notes.

    We put them in, but if we did them for you, that would be like having someone else do your workouts for you. And don’t just look at the exercises. Use a pencil. There’s plenty of evidence that physical activity while learning can increase the learning.

  3. Read the “There are No Dumb Questions”

    That means all of them. They’re not optional sidebars, they’re part of the core content! Don’t skip them.

  4. Make this the last thing you read before bed. Or at least the last challenging thing.

    Part of the learning (especially the transfer to long-term memory) happens after you put the book down. Your brain needs time on its own, to do more processing. If you put in something new during that processing time, some of what you just learned will be lost.

  5. Talk about it. Out loud.

    Speaking activates a different part of the brain. If you’re trying to understand something, or increase your chance of remembering it later, say it out loud. Better still, try to explain it out loud to someone else. You’ll learn more quickly, and you might uncover ideas you hadn’t known were there when you were reading about it.

  6. Drink water. Lots of it.

    Your brain works best in a nice bath of fluid. Dehydration (which can happen before you ever feel thirsty) decreases cognitive function.

  7. Listen to your brain.

    Pay attention to whether your brain is getting overloaded. If you find yourself starting to skim the surface or forget what you just read, it’s time for a break. Once you go past a certain point, you won’t learn faster by trying to shove more in, and you might even hurt the process.

  8. Feel something.

    Your brain needs to know that this matters. Get involved with the stories. Make up your own captions for the photos. Groaning over a bad joke is still better than feeling nothing at all.

  9. Get your hands dirty!

    There’s only one way to learn data analysis: get your hands dirty. And that’s what you’re going to do throughout this book. Data analysis is a skill, and the only way to get good at it is to practice. We’re going to give you a lot of practice: every chapter has exercises that pose a problem for you to solve. Don’t just skip over them—a lot of the learning happens when you solve the exercises. We included a solution to each exercise—don’t be afraid to peek at the solution if you get stuck! (It’s easy to get snagged on something small.) But try to solve the problem before you look at the solution. And definitely get it working before you move on to the next part of the book.

Read Me

This is a learning experience, not a reference book. We deliberately stripped out everything that might get in the way of learning whatever it is we’re working on at that point in the book. And the first time through, you need to begin at the beginning, because the book makes assumptions about what you’ve already seen and learned.

This book is not about software tools.

Many books with “data analysis” in their titles simply go down the list of Excel functions considered to be related to data analysis and show you a few examples of each. Head First Data Analysis, on the other hand, is about how to be a data analyst. You’ll learn quite a bit about software tools in this book, but they are only a means to the end of learning how to do good data analysis.

We expect you to know how to use basic spreadsheet formulas.

Have you ever used the SUM formula in a spreadsheet? If not, you may want to bone up on spreadsheets a little before beginning this book. While many chapters do not ask you to use spreadsheets at all, the ones that do assume that you know how to use formulas. If you are familiar with the SUM formula, then you’re in good shape.

This book is about more than statistics.

There’s plenty of statistics in this book, and as a data analyst you should learn as much statistics as you can. Once you’re finished with Head First Data Analysis, it’d be a good idea to read Head First Statistics as well. But “data analysis” encompasses statistics and a number of other fields, and the many non-statistical topics chosen for this book are focused on the practical, nitty-gritty experience of doing data analysis in the real world.

The activities are NOT optional.

The exercises and activities are not add-ons; they’re part of the core content of the book. Some of them are to help with memory, some are for understanding, and some will help you apply what you’ve learned. Don’t skip the exercises. The crossword puzzles are the only thing you don’t have to do, but they’re good for giving your brain a chance to think about the words and terms you’ve been learning in a different context.

The redundancy is intentional and important.

One distinct difference in a Head First book is that we want you to really get it. And we want you to finish the book remembering what you’ve learned. Most reference books don’t have retention and recall as a goal, but this book is about learning, so you’ll see some of the same concepts come up more than once.

The book doesn’t end here.

We love it when you can find fun and useful extra stuff on book companion sites. You’ll find extra stuff on data analysis at the following url: http://www.headfirstlabs.com/books/hfda/.

The Brain Power exercises don’t have answers.

For some of them, there is no right answer, and for others, part of the learning experience of the Brain Power activities is for you to decide if and when your answers are right. In some of the Brain Power exercises, you will find hints to point you in the right direction.

The technical review team

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Eric Heilman

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Bill Mietelski

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Tony Rose

Technical Reviewers:

Eric Heilman graduated Phi Beta Kappa from the Walsh School of Foreign Service at Georgetown University with a degree in International Economics. During his time as an undergraduate in DC, he worked at the State Department and at the National Economic Council at the White House. He completed his graduate work in economics at the University of Chicago. He currently teaches statistical analysis and math at Georgetown Preparatory School in Bethesda, MD.

Bill Mietelski is a Software Engineer and a three-time Head First technical reviewer. He can’t wait to run a data analysis on his golf stats to help him win on the links.

Anthony Rose has been working in the data analysis field for nearly ten years and is currently the president of Support Analytics, a data analysis and visualization consultancy. Anthony has an MBA concentrated in Management and Finance degree, which is where his passion for data and analysis started. When he isn’t working, he can normally be found on the golf course in Columbia, Maryland, lost in a good book, savoring a delightful wine, or simply enjoying time with his young girls and amazing wife.

Acknowledgments

My editor:

Brian Sawyer has been an incredible editor. Working with Brian is like dancing with a professional ballroom dancer. All sorts of important stuff is happening that you don’t really understand, but you look great, and you’re having a blast. Ours has been a exciting collaboration, and his support, feedback, and ideas have been invaluable.

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The O’Reilly Team:

Brett McLaughlin saw the vision for this project from the beginning, shepherded it through tough times, and has been a constant support. Brett’s implacable focus on your experience with the Head First books is an inspiration. He is the man with the plan.

Karen Shaner provided logistical support and a good bit of cheer on some cold Cambridge mornings. Brittany Smith contributed some cool graphic elements that we used over and over.

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Really smart people whose ideas are remixed in this book:

While many of big ideas taught in this book are unconventional for books with “data analysis” in the title, few of them are uniquely my own. I drew heavily from the writings of these intellectual superstars: Dietrich Doerner, Gerd Gigerenzer, Richards Heuer, and Edward Tufte. Read them all! The idea of the anti-resume comes from Nassim Taleb’s The Black Swan (if there’s a Volume 2, expect to see more of his ideas). Richards Heuer kindly corresponded with me about the book and gave me a number of useful ideas.

Friends and colleagues:

Lou Barr’s intellectual, moral, logistical, and aesthetic support of this book is much appreciated. Vezen Wu taught me the relational model. Aron Edidin sponsored an awesome tutorial for me on intelligence analysis when I was an undergraduate. My poker group—Paul, Brewster, Matt, Jon, and Jason—has given me an expensive education in the balance of heuristic and optimizing decision frameworks.

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People I couldn’t live without:

The technical review team did a brilliant job, caught loads of errors, made a bunch of good suggestions, and were tremendously supportive.

As I wrote this book, I leaned heavily on my friend Blair Christian, who is a statistician and deep thinker. His influence can be found on every page. Thank you for everything, Blair.

My family, Michael Sr., Elizabeth, Sara, Gary, and Marie, have been tremendously supportive. Above all, I appreciate the steadfast support of my wife Julia, who means everything. Thank you all!

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