Head First Data Analysis: A learner's guide to big numbers, statistics, and good decisions 1st Edition

This was a beautiful book that really refueled my interest for Statistics (which I've been struggling to start learning...even though I know calculus and LOVE mathematics)...but it really caught my eye because it goes into detail about the R statistical programming language.The first few chapters get you going on a specific mindset of how to interpret data, which is VERY important to keep throughout the entire reading of this book.After that groundwork is established, you are taken on a really cool journey of some Excel features (don't freak out...those of you who don't know excel proficiently will be fine in the hands of this book) that you never would've believed were there! You can even use Google Docs to do the same things if you don't have a valid copy of Excel!Finally, R comes into play with all its glory...I would've loved for a deeper dive with this technology, but there are several other books out there in which you can get down and dirty with R (http://www.amazon.com/The-Art-Programming-Statistical-Software/dp/1593273843/ and http://www.amazon.com/Cookbook-OReilly-Cookbooks-Paul-Teetor/dp/0596809158/ are my favorites and I own them both on my kindle).I hope that eliminates all your FUD's (Fears, Uncertainties, and Doubts)...go and grab this book RIGHT NOW! You'll be blown away with what you'll be able to do after you read everything here!P.S. It only takes about a week and a half to get through it going at a nice, slow, and comfortable pace...if you're HUNGRY like I was, you can knock it out in about 4 days.

I got the book promptly. It has that softbound textbook feel. but good binding not cheap or ready to fall apart. the intormation in it so far seems interesting and well organized. its in the "head first format" which means there is a lot of nice visual lay out and side notes and some graphics to make understanding the concepts by seeing them when possible. I like that format. It is still pretty clean and gets to the point. but I have only read and used so much of it at this point so I cannot go much farther into the content than that. -- in short I think it is a solid book to get if one wants to better understand how to interpret social science numbers, or other scientific numbers that they are shown in a way that they are wise to various ways that data can be spiked and spiced. how in depth I cannot comment on as I have not fully digested the book. But it is a book that is designed to be both read and used as a topical reference. And it has the "Head First" style keeping things clean but providing insightful commentary, context and graphical illustrations where it might really speed up or enhance understanding of a particular idea or complicated example. it also uses bolding in areas where you can pay attention to the new vocabulary you might want to learn in order to lay the ground work for even more technical education in data analysis. it even has a chapter where it goes over some of the more obscure plug ins for excel that are there for helping a person analyze data. I would basically treat this book as a nice survey of both the human technical sides of data analysis. it also covers things like data collection or effective data presentation, and as I said it refers to several readily available tools like excel for example and how they can be used by someone who wanted to know how to leverage their computer in order tame and extract meaning from data they have been given to interpret. -- I think that its a useful primer that is like a survey course in the subject sans the professor. But how good each section is I cannot comment on as I have only started with the book for a several weeks. but what I did read I found completely intelligible and because I am not a total novice at looking at Data, there were times I could use its nice formatting to skip past explanations I did not need because I already was familiar with them. If I fall in love with the book I may come back and say so and make my stars 5 instead of a 4 but at this point I would highly recommend this book for anyone who wanted a nice primer that went into to a very serviceable level of detail for a primer or survey type information source.

Different problems need different methods to be solved properly. This book takes various examples and lets the reader work through the problems. It is actually fun to read this book. Very well explained. Of course, not all the problems worked 100%, but I have not read a book with examples and problems that all work. Especially, some of my R did not work too well. Other than that it is a great book, and a great way to learn about data analysis.

SQL in legman’s terms. Very helpful.

Going through this book for introductory Data Analysis elements has been extremely helpful, especially in later chapters utilizing "R".Pros:1) Great introductory material to Data Analysis, including reporting techniques and later chapters including hands on examples utilizing "R".2) Extremely easy read, was able to cover the material in the span of 1-2 work days and feel as though most of the information has been absorbed.Cons:1) The binding is really poor (it might just be my copy). When I opened the book I had a handful of pages just fall out. I needed the book for work, so there wasn't much of an option to wait while returning it. I'll just have to fix the binding myself later.2) Multiple areas that have typos or missing data. For the most part I was able to figure out what was being explained, but some links for data were incorrect.Wishes:1) A section containing data collection techniques would have been wonderful. Sometimes you aren't given the data, and are expected to retrieve the data needed for analysis.2) A section covering creating models and analysis based on best/worst/average case estimates from subject matter experts. What to do while waiting for needed data.Aside from the glaring issues mentioned, I would still recommend this book to anyone who needs an introductory book to Data Analysis.