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Advanced Excel for Scientific Data Analysis
cgjherr writes "If the recent financial meltdown has left you wondering, 'When does exponential decay function stop?' then I have the book for you. Advanced Excel for Scientific Data Analysis is the kind of book that only comes along every twenty years. A tome so densely packed with scientific and mathematical formulas that it almost dares you to try and understand it all. A "For Dummies" book starts with a gentle introduction to the technology. This is more like a "for Mentats" book. It assumes that you know Excel very well. The first chapter alone will have you in awe as you see the author turn the lowly Excel into something that rivals Mathematica using VBA, brains, and a heaping helping of fortitude." Read on for the rest of Jack's review.
Advanced Excel for Scientific Data Analysis
author
Robert de Levie
pages
700
publisher
Oxford Press
rating
9
reviewer
Jack Herrington
ISBN
9780195370225
summary
Use Excel for high end scientific data analysis akin to Mathemetica
When I first opened this book my mouth just dropped. It had been years since I had seen a book typeset using LaTeX. But in an instant it made sense as the book is crammed packed with the kind of equations that would have been a nightmare to build with any other tools. Chapter after chapter has everything a really smart person needs to do curve fitting, statistical measures, differential equations, time-frequency analysis. But don't expect a play by play here. You will get the equations, set within a few dense paragraphs, with maybe a spreadsheet and a chart or two to show the results.
The first chapter concentrates on the getting the most out of Excel as a tool. All the chapters that follow dig into specific data analysis techniques. Chapters two, three and four are on least squares. Chapter five and six cover the analysis in the time domain including fourier transforms. Chapter seven covers differential equations. Chapter eight returns to Excel by digging in deeper into macros. Which leads into chapter nine, where we dig deeper into basic mathematical operations. Chapter ten covers matrix operations. And chapter eleven wraps it all up by giving you some spreadsheet best practices.
In University style there are also some exercises that you can do along the way if you want to tweak your brain pan a little more. To amuse myself I tried a few and I believe the book would have assessed my attempts 'wanting' if it had a voice to tell me.
Where most books like this would have several authors this book has just one; Roberte de Levie. This means that the tone, style and quality of the book is consistent throughout. A fact that you will come to appreciate as the book wades in ever increasingly deep data analysis concepts as the chapters roll on.
Though I would have preferred the book to have code samples in C#, I understand that the language of Excel is VBA and I guess I have to live with that. Thankfully VBA has come a long way and if you so inclined it would likely be easy to translate the code into C#, Java, or whatever else you like.
The fact that one person wrote the book left me wondering, "Who is this guy?" In my minds eye I kinda of figured he would look like one of those pulsing brain guys from Star Trek. Turns out he is a professor at Bowdoin College. And his fields of study include ionic equilibria, electrochemical kinetics, electrochemical oscillators, stochastic processes, and a whole lot more stuff that almost seems made up to sound impressive.
When this book isn't serving as an amazing reference for both Excel, scientific problem solving, or just insane equations it serves other purposes as well. It's a handy portable IQ test, as the count of pages you can grind through in one sitting, plus 90, is roughly your intelligence quotient. And if you fail at that you can always put a copy of the book, along with the Orange Bible, under your pillow and try to osmose your way to becoming the Kwisatz Haderach.
In all seriousness, this is a great book. It represents the kind of in-depth work and research we used to see in books that came out twenty years ago. Robert is to be applauded for his work. This is an excellent resource for anyone looking to do scientific data analysis but who was unaware of the powerful capabilities that Excel provides that is likely waiting just one Startup menu click away.
The book is not without fault. I would have preferred that it had been in color, or at least have one color section to show some of the more impressive visualizations that I'm sure would look great in color. In addition the index is silly short for a book that clocks in at 700 pages. But those are only minor quibbles for what is all-in-all an amazing piece of work.
You can purchase Advanced Excel for Scientific Data Analysis from amazon.com. Slashdot welcomes readers' book reviews -- to see your own review here, read the book review guidelines, then visit the submission page.
The first chapter concentrates on the getting the most out of Excel as a tool. All the chapters that follow dig into specific data analysis techniques. Chapters two, three and four are on least squares. Chapter five and six cover the analysis in the time domain including fourier transforms. Chapter seven covers differential equations. Chapter eight returns to Excel by digging in deeper into macros. Which leads into chapter nine, where we dig deeper into basic mathematical operations. Chapter ten covers matrix operations. And chapter eleven wraps it all up by giving you some spreadsheet best practices.
In University style there are also some exercises that you can do along the way if you want to tweak your brain pan a little more. To amuse myself I tried a few and I believe the book would have assessed my attempts 'wanting' if it had a voice to tell me.
Where most books like this would have several authors this book has just one; Roberte de Levie. This means that the tone, style and quality of the book is consistent throughout. A fact that you will come to appreciate as the book wades in ever increasingly deep data analysis concepts as the chapters roll on.
Though I would have preferred the book to have code samples in C#, I understand that the language of Excel is VBA and I guess I have to live with that. Thankfully VBA has come a long way and if you so inclined it would likely be easy to translate the code into C#, Java, or whatever else you like.
The fact that one person wrote the book left me wondering, "Who is this guy?" In my minds eye I kinda of figured he would look like one of those pulsing brain guys from Star Trek. Turns out he is a professor at Bowdoin College. And his fields of study include ionic equilibria, electrochemical kinetics, electrochemical oscillators, stochastic processes, and a whole lot more stuff that almost seems made up to sound impressive.
When this book isn't serving as an amazing reference for both Excel, scientific problem solving, or just insane equations it serves other purposes as well. It's a handy portable IQ test, as the count of pages you can grind through in one sitting, plus 90, is roughly your intelligence quotient. And if you fail at that you can always put a copy of the book, along with the Orange Bible, under your pillow and try to osmose your way to becoming the Kwisatz Haderach.
In all seriousness, this is a great book. It represents the kind of in-depth work and research we used to see in books that came out twenty years ago. Robert is to be applauded for his work. This is an excellent resource for anyone looking to do scientific data analysis but who was unaware of the powerful capabilities that Excel provides that is likely waiting just one Startup menu click away.
The book is not without fault. I would have preferred that it had been in color, or at least have one color section to show some of the more impressive visualizations that I'm sure would look great in color. In addition the index is silly short for a book that clocks in at 700 pages. But those are only minor quibbles for what is all-in-all an amazing piece of work.
You can purchase Advanced Excel for Scientific Data Analysis from amazon.com. Slashdot welcomes readers' book reviews -- to see your own review here, read the book review guidelines, then visit the submission page.
Don't do it!
"The first chapter alone will have you in awe as you see the author turn the lowly Excel into something that rivals Mathematica using VBA, brains, and a heaping helping of fortitude."
Then why not just use Mathematica?
So? What's so special about that? You can turn C, Fortran, or even assembly language into something that rivals Mathematica using brains and a heaping helping of fortitude. This is arguably a better deal, since you don't need the VBA.
--MarkusQ
...everything looks like a snowglobe!
Hardcore data analysis in Excel is almost always a bad idea. You can almost always find a way to do it in excel, and you can almost always find a way to do it better, faster, and cheaper somewhere else.
R, MatLab, Mathemateica, Python/Numpy, SigmaPlot, and any number of old, well written, debugged and vetted numerical libraries written in C or Fortran. I've used all of these at various times to solve something that a co-worker couldn't figure out how to do in Excel.
I fit quick linear regressions in Excel. For *anything* else, there is a better choice.
-V-
Who can decide a priori? Nobody.
-Sartre
for scientific data analysis.
I know it is popular and many science and engineering faculty lazily encourage their graduate students to use it. However, something like matlab beats the crap out of excel any day. Spreadsheets tend to obfuscate relationships between data, require a lot more clicking (read human intervention) and waste time that could be spent thinking about the data, and are singularly unsuited for analysis of similar sets of data (a situation any scientist faces when he has to do a series of experiments).
Matlab might take sometime to initially write the scripts, but it is so powerful and extensible that no one in their right mind would want to use excel. If you are a slave to spreadsheets, get yourself a copy of Microcal Origin or Labplot.
Excel is especially unsuited to the task of preparing figures for scientific publications. The default formatting is at once wrong for the task and hard to change. Once you set your preferences in matlab (easy to do), you are set for life.
In my experience, excel is also rarely used for anything serious outside of US. Maybe its an indictment of how lazy, slow witted and easily misled our pool of talent is becoming.
Well, I do put faith into my fortran compiler.
...in the same way that MS paint is as capable as photoshop...
Yes, I use both. LaTeX if I have a choice, Word if I need to exchange docs with less enlightened colleagues.