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Head First Data Analysis: A learner's guide to big numbers, statistics, and good decisions (Englisch) Taschenbuch – 19. August 2009

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Produktinformation

  • Taschenbuch: 492 Seiten
  • Verlag: O'Reilly and Associates; Auflage: 1 (19. August 2009)
  • Sprache: Englisch
  • ISBN-10: 0596153937
  • ISBN-13: 978-0596153939
  • Größe und/oder Gewicht: 20,3 x 2,5 x 23,5 cm
  • Durchschnittliche Kundenbewertung: 5.0 von 5 Sternen  Alle Rezensionen anzeigen (4 Kundenrezensionen)
  • Amazon Bestseller-Rang: Nr. 10.603 in Fremdsprachige Bücher (Siehe Top 100 in Fremdsprachige Bücher)

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Produktbeschreibungen

Synopsis

This book is for anyone who deals with data. That's most of us, so wouldn't it be great if you could deal with that data faster and more effectively? "Head First Data Analysis" is a practical title that guides you through all facets of data analysis; dealing with people who gather information, then sorting and cleaning the data. Once you've got your base data, you'll look through it to find patterns, tell stories, map space and time, and even predict the future. You already know a lot about how to tell stories with information, couple that skill with the tools you'll learn in this book and you'll be able to make smarter decisions based on your analysis. You'll be able use your creativity to gain profound insights into how your business works and where it's going through novel, interesting judgements about the data you want to understand. If you actively tell stories with data, rather than merely grinding out 'canned routines', you'll be better understood by your consumers and better able to make real substantive claims about the data. This book will help you do that using the tried and tested Head First methodology and visually rich format designed for the way your brain works.

Based on the latest research in neurobiology, cognitive science, and learning theory, this book combines words and pictures in a playful, mixed-media style that not only helps you understand data analysis, but also to remember it. And along the way, you'll learn how to apply these theories to your own analysis!

Über den Autor und weitere Mitwirkende

Michael Milton likes books. Before his first day of high school wrestling, he checked out a stack of books on technique from the library and practiced on his not-terribly-enthusiastic little sister. Then he spent the first few minutes of tryouts kicking the butts of other newbies, until the experienced wrestlers realized how much fun it would be to kick his. Within a few months, he became a decent wrestler, but he always stayed a bit ahead of the other newbies because of those books. His life has consisted of gleefully going through that process over and over again in completely unrelated fields. Naturally, he's a Head First fanatic. Until recently Michael spent most of time looking at databases to help nonprofit organizations figure out how to make more money. He has a degree in philosophy from New College of Florida and one in religious ethics from Yale University. When he's not in the library or the bookstore, you can find him in-line skating, taking pictures, and brewing beer.

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7 von 9 Kunden fanden die folgende Rezension hilfreich Von gweep am 19. September 2010
Format: Taschenbuch
Seit Anbeginn der Zeit hat der Mensch Daten gesammelt und Daten analysiert.
Seit dem Zeitalter der Computer werden mehr und mehr Daten gesammelt und ausgewertet. Daten an sich können sowohl Zahlen als auch Informationen sein. Der Staat sammelt Daten zu seinen Bürgern, seinen politischen Gegnern - Firmen über Mitarbeiter, Kunden - Ausgaben, Einnahmen etc. Und all diese Daten müssen einem Zweck dienen, Informationen daraus zu erhalten. Der Staat will wissen, wie viele Bürger männlich sind, wie viele weiblich, wo die meisten Menschen Wohnen, warum sie dort Wohnen, warum andere Orte nicht vom Interesse sind, obwohl dort die Lage besser wäre - die Firmen wie die Umsatzzahlen ihrer Mitarbeiter sind, warum Produkte nicht so greifen, wie sie sollen, der Administrator warum und wann der Mail-Server aussetzt, warum die Benutzer im Netzwerk über dies oder jenes Problem, immer zur selben Zeit klagen.
Und auch wenn wir nur einkaufen gehen, so nehmen wir, meist aus den Werbeprospekten schon Datenanalyse vor, indem wir die Preise vergleichen. Je mehr Daten zusammen kommen, desto unübersichtlicher werden diese. Es gilt also, die Daten zu analysieren und jene Daten aus den vielen Informationen zu entnehmen, die für die Analyse entscheidend sind.

Diese Information finden sie in diesem Buch und in jedem anderen auch. Aber ...
Wie werden Daten richtig analysiert? Wer Daten analysieren muss und die Ursache für gewisse Vorgänge suchen bzw. untersuchen muss, wird es mit den Daten alleine nicht weit bringen. Man kann also Daten nur dann richtig verarbeiten, wenn man weiß, welche Daten relevant sind und genügend Informationen zu dem jeweiligen Thema hat.
Lesen Sie weiter... ›
Kommentar War diese Rezension für Sie hilfreich? Ja Nein Feedback senden...
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Wir konnten Ihre Stimmabgabe leider nicht speichern. Bitte erneut versuchen
Von NS am 19. Februar 2013
Format: Taschenbuch Verifizierter Kauf
Easy to understand, they tried to include the most important parts and programs (excel, R). A very good introduction book to data analysis and perfect for 'filling the wholes' in case something is missing in the knowledge about data analysis. It is highly preferred to be combined with Head First Statistics, since basic knowledge in statistics is a must for this book.

In general - very satisfied from these book series!
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Format: Taschenbuch
Ich verwende dieses Buch zur Ausbildung von Studenten und bin begeistert. Es ist didaktisch hervorragend geschrieben und vermittelt eine komplizierte Materie auf anschauliche Weise. Aus meiner Sicht absolut empfehlenswert.
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0 von 26 Kunden fanden die folgende Rezension hilfreich Von Mofasa am 9. November 2009
Format: Taschenbuch
Der Anbieter war sehr zuverlässig! Und das Buch ist auch sehr gut und interessant. Leider entspricht es nicht ganz meinen Bedürfnissen, aber ich denke, dass es seinen Nutzen trotzdem haben wird.
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Die hilfreichsten Kundenrezensionen auf Amazon.com (beta)

Amazon.com: 34 Rezensionen
56 von 58 Kunden fanden die folgende Rezension hilfreich
Combines mathematics, tools, and tactics 30. August 2009
Von calvinnme - Veröffentlicht auf Amazon.com
Format: Taschenbuch
This book is for professionals that must analyze data in their daily work. First off, if you are unfamiliar with the approach of the "Head First" series of books by O'Reilly, the approach was and is revolutionary in the field of technical writing. The authors of this series know that page after page of terse text will not easily penetrate the brain of the working professional who needs help rather quickly. Traditional textbook models work best on students in a traditional classroom setting who can slowly absorb material over a period of several months with the help of bi-weekly classroom sessions with a professor. The working professional does not have this luxury of time or of personal tutoring.

Thus the authors both penetrate your brain and hold your interest by serving information up in unusual ways - odd pictures and illustrations, Q&A sessions, repeating the same material in different ways, and interesting case studies in which you are asked at every step to give your input. They'll even lead you down the the wrong path every now and then so that you remember the right one all the better.

As for the subject matter, this is not a book on statistics and how to solve problems in statistics. Instead, it is how you use various statistical models and tools and visualization to analyze often confusing corporate data and come up with recommendations based on that data. Some mathematical methods will be presented as they are necessary to solving the underlying problems - optimization, hypothesis testing, bayesian statistics, subjective probabilities, heuristics, and histograms - these are all mentioned and even have their own chapters. However, this book is also about tools - R and the analysis tools of Excel specifically. In the appendix, this book even shows you how to install R.

However, I don't believe that you could get away with knowing nothing of statistics and really get the most out of this book. If you do happen to have the luxury of a little time I suggest the following. Read the excellent Head First Statistics as a tutorial, and then use the problems in Schaum's Outline of Statistics (Schaum's Outline Series) to test your knowledge. Then you should be more than ready for this book.

The author has a chapter entitled "leftovers" that tells you what this book does not cover. I include that here so that you don't waste your time if this is what you are looking for:

1 Everything else in statistics
2 Excel skills - (book assumes previous experience)
3 Edward Tufte and his principles of visualization
4 PivotTables
5 Nonlinear and multiple regression
7 Null-alternative hypothesis testing
8 Randomness
9 Google Docs

I highly recommend this book for the right audience with the right experience level.
25 von 28 Kunden fanden die folgende Rezension hilfreich
Slice and dice data like a Ninja 24. August 2009
Von Bill Mietelski - Veröffentlicht auf Amazon.com
Format: Taschenbuch
First, a disclaimer: as one of the technical reviewers for the book, I might be a little biased. Having said that, I'm willing to bet my copy of Head First Data Analysis that this won't be the last 5-star review you'll find here :-)

By my count this is the 20th book in the Head First series, so by now most Amazon customers know the story behind the Head First format, style, and pedagogy. These aren't your typical technical books, so if this is the first Head First book you're considering, you owe it to yourself to get a sneak preview first. I think you'll be in for a treat.

The Amazon Reader does have the first six pages of Chapter 1, which will give you some idea, but I'd recommend going to Head First Labs where you can download and read the entire 2nd chapter. You can also grab the full Table Of Contents in PDF format, which I believe is a little easier on the eyes than the TOC in the Amazon Reader.

The book is written for folks without hardcore data analysis experience who are looking for an introduction to analyzing data to make better decisions. You won't need a background in statistics, engineering, or computer science. While some data analysis books assume you're a math geek, Michael Milton does not.

And while many "Data Analysis" books pretty much revolve around Excel's data analysis functions (Analysis ToolPak, Solver, etc), this book is more about how you work with data, not about how you use a particular software tool. While you do use spreadsheets and a statistical computing software package called "R", the focus is on using the tools between your ears to become a better data analyst.

These days almost everyone needs to deal with and interpret data. Those that become successful know how to make sense of it all. This book will help you think about, process, and present your data so you can draw reliable conclusions to real-life questions.
23 von 26 Kunden fanden die folgende Rezension hilfreich
Too much fluff 15. Februar 2011
Von Gregory A. Stobbs - Veröffentlicht auf Amazon.com
Format: Taschenbuch Verifizierter Kauf
While some of the Head First series have been quite helpful, this one has way too much fluff, making it tedious to find the important content. By way of example, the entire page 97 is devoted to "Profits fell through the floor" with a picture of a sad person, a picture of a pile of rubber ducks, a sample letter expressing a complaint, and the conclusion that "this is pretty bad news." Page 97 lies in the middle of the "optimization" chapter, but you don't get to the punch line on what to do about the "pretty bad news" until page 108. The pace of the book is simply too slow--which I attribute to an overuse of the Head First style, a style supposedly "designed for the way your brain works." My brain would have been happier if the editors had picked up the pace.
14 von 15 Kunden fanden die folgende Rezension hilfreich
Transforming Data Into Better Decision Making 21. August 2009
Von Ira Laefsky - Veröffentlicht auf Amazon.com
Format: Taschenbuch
Like the rest of the excellent Head First Series this volume provides excellent planned pedagogy (teaching) in the field it addresses.
But, this excellence has been put to a harder test in this volume that asks: "How do I find, analyze and present the data which will answer the questions being asked by business leaders, scientists and policy makers?". It begins with an excellent introductory section (that easily could be turned into a book of its own) about how business and policy questions and undefined verbal problems can be analyzed and directed toward the data which will provide an accurate answer to the underlying question. It proceeds to design of data-based experiments, hypothesis testing and the appropriate statistical techniques which will provide accurate and easily understandable analysis. While there is a certain amount of data-based experimental design which is presented in introduction, the statistical methods are presented together with the tools that will allow anyone with a basic quantitative intuition to analyze complex data with Excel spreadsheets and the "R" statistical language. Data visualizations of quantitative information, data cleaning and representation of relational databases are presented in a light that will lead to accurate analysis and clear conclusions, as opposed to beautiful information visualizations for their own sake.

This volume will be a valuable educational tool and reference for future generation of business and policy analysts, as well as anyone who must find and communicate the answers to difficult questions based upon numerical and data-based analysis. This book illustrates that the Head First editorial format can be excellently applied to real life decision making and analysis issues as well as it has previously been employed in teaching high school and university subject matter.
10 von 11 Kunden fanden die folgende Rezension hilfreich
An easy to read introductory book with no details 31. Oktober 2009
Von Bin Hu - Veröffentlicht auf Amazon.com
Format: Taschenbuch
Skip this book if you really want to know how data analysis is done. Read it if you only want to get a quick look at what data analysis is about. This book covers no details. For example, in chapter 3, optimization, the author did a good job in introducing readers the idea (not the concept) of optimization and how to do it using Excel. But what is the algorithm behind the Excel solver? Or, how Excel solve the problem? Nothing is provided in the book.
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