Head First Data Analysis: A Learner's Guide to Big Numbers, Statistics, and Good Decisions

Head First Data Analysis A Learner s Guide to Big Numbers Statistics and Good Decisions Today interpreting data is a critical decision making factor for businesses and organizations If your job requires you to manage and analyze all kinds of data turn to Head First Data Analysis where

  • Title: Head First Data Analysis: A Learner's Guide to Big Numbers, Statistics, and Good Decisions
  • Author: Michael G. Milton
  • ISBN: 9780596153939
  • Page: 431
  • Format: Paperback
  • Head First Data Analysis: A Learner's Guide to Big Numbers, Statistics, and Good Decisions

    Today, interpreting data is a critical decision making factor for businesses and organizations If your job requires you to manage and analyze all kinds of data, turn to Head First Data Analysis, where you ll quickly learn how to collect and organize data, sort the distractions from the truth, find meaningful patterns, draw conclusions, predict the future, and present yourToday, interpreting data is a critical decision making factor for businesses and organizations If your job requires you to manage and analyze all kinds of data, turn to Head First Data Analysis, where you ll quickly learn how to collect and organize data, sort the distractions from the truth, find meaningful patterns, draw conclusions, predict the future, and present your findings to others Whether you re a product developer researching the market viability of a new product or service, a marketing manager gauging or predicting the effectiveness of a campaign, a salesperson who needs data to support product presentations, or a lone entrepreneur responsible for all of these data intensive functions and , the unique approach in Head First Data Analysis is by far the most efficient way to learn what you need to know to convert raw data into a vital business tool You ll learn how to Determine which data sources to use for collecting information Assess data quality and distinguish signal from noise Build basic data models to illuminate patterns, and assimilate new information into the models Cope with ambiguous information Design experiments to test hypotheses and draw conclusions Use segmentation to organize your data within discrete market groups Visualize data distributions to reveal new relationships and persuade others Predict the future with sampling and probability models Clean your data to make it use

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    Head First Data Analysis: A Learner's Guide to Big Numbers, Statistics, and Good Decisions

    One thought on “Head First Data Analysis: A Learner's Guide to Big Numbers, Statistics, and Good Decisions

    1. Franco Arda

      I wish I had this book during my MBA.Rather then another praise for this great Head First book, some really good topics in this book Chapter 2 TEST YOUR THEORIESHow to use the method of comparison and make them explicit.Chapter 5 HYPOTHESIS TESTINGFalsification vs satisficing Falsification as the heart of hypothesis testing.Chapter 6 BAYESIAN STATISTICSAh, the problem with the first base I ve never seen a better explanation of the Bayes rule.Chapter 7 SUBJECTIVE PROBABILITIESThe subject of incec [...]

    2. Terry

      Decent book Some typos, but not unrecoverable to get at what is needed Some presumption of MS Excel knowledge A bit dated, since MS forces you to use the StatPlus package, no longer offering the Data Analysis add on It will definitely be a jump off point to diving into Stats and Analysis work R seems powerful and the one great example at the end of the book showed me some great hotness graphically It is a good workout.

    3. Jean-Luc

      A while ago, I read an article that said statistician is the hottest growing field, so I picked up this book.And I don t remember even one thing from this book, other than it used a mix of Excel and R to get the job done The lack of memory says about me than about the book I ll have to pick it up again and re read it This is just a placeholder.

    4. Ws

      A basic but good primer on data analysis, good for getting started I like the tips pages and there are no stupid questions.If you re looking for something technical and specific, this book won t cover much, use it like as a starting point.

    5. Ajita Gupta

      The book provides an excellent overview of the basic mathematical concepts randomization, hypothesis testing, regression, bayes , terminology optimization function constraints, heuristics, pruning as well as common tools R, excel and use cases for everyday problems in Data Analytics.

    6. Jason Hardin

      Good basic overview of analytical techniques with excel and R I would recommend this to someone who hasn t reviewed statistics in a while or is just looking for a start in regression analysis and a couple other techniques.

    7. Jerzy

      Not read, just skimmed I skimmed this as a statistician looking for ideas on how to teach Stats 101 This is not purely stats maybe like Data Science, since it also includes very useful things like optimization and databases.It seems to cover the most important stats concepts without going deep into details of p values and such.I m not sure about the silly pictures and word bubbles or contrived examples, but I love that designing experiments is already in the 2nd chapter, after a 1st chapter on [...]

    8. zedoul

      Do not get fooled about the star I had given to it This is not a bad book, it is just matter of quality it pursues This is quite good book with regards to its aim newbies who would like to understand what happens in data analysis, and eventually forget it after reading Because the book is than glorified version of help documents, and less than a academic, hard to read books as it used to be I mean the book is not recommendable to whom seriously want to study it, with statistical basis.

    9. Gaurav Mathur

      Very slow, very dumbed down.The case approach is good, but they can give it a better pace Gave this up twice out of sheer boredom, but finally completed Also, had many obvious errors.Some parts might useful for an ABSOLUTE beginner to Data Analysis.A lot of advanced topics were mentioned which were not dealt in depth.My only takeaway it got me started with R.

    10. Eric Wallace

      Much simplistic than I was expecting, as it merely grazes a few basic concepts I was hoping for content on statistics and using the R software, but I ll have to seek that elsewhere Nevertheless, the Head First series of books are easy to read and occasionally mildly amusing too , so this was a breeze.

    11. Christian Brumm

      Gute Einfuehrung in die Datenanalyse im gewohnten heads first format Gehirnfreundlich und unserioes Auf Verstaendnis einiger grundlegender Konzepte e.g Regression, Bayes und minimale Einfuehrung in einige Tools R, Datenbanken ausgerichtet Netter Ueberblick, natuerlich nicht allzuviel Tiefe.

    12. Daniel Christensen

      Started reading this when I joined Institute for Child Health Research It s not overly technical, but it keeps you focused on the basics ask the right questions and use lots it pictures.Excellent training wheels.

    13. Daniel Galassi

      This book covers a wide range of topics with a good balance of depth and non academic scenarios It will not make the reader a mathematician but it will certainly introduce them to a variety of data analysis tools.

    14. Mattias

      Very basic stuff, but a really good starting point for people wanting to learn about data analysis in general Accessible, but still deals with a host of important issues in a good way You don t come by that often in this particular domain of knowledge.

    15. Isk

      Super basic, so I didn t really learn anything new , but I guess I got a better idea of what analysts are actually supposed to do.I also liked the idea of the presentation, though a lot of it looks kinda tacky.

    16. Pascal

      Not a bad introduction to data analysis, a little on the basic side, not sure how much will translate to actual work.

    17. Noelle

      Hard to get into this if you don t have some time dedicated to reading and going through the exercises Good examples and use cases

    18. Kevin Powe

      Great primer on data analysis with a perfect mix of theoretical and practical, as always for the Head First range.

    19. Hayyu Alynda

      Bagus dan cara penyajiannya sangat menarik tapi isinya banyak yang diulang ulang Penting buat basic knowledge data analysis.

    20. Renanreismartins

      I could not finish this book, it is kind of boring and tedious, so I stopped at page 272 I was expecting math explanations, but the book is conceptual and really superficial.

    21. Bálint

      Really liked it HF s approach is great and this is a great, hand on intro to Data Analysis It gives a great overview upon which it s easy to expand Diving into Head First Statistics now.

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