I received yesterday a copy of the brand-new book by Ilya Narsky and Frank Porter, "Statistical Analysis Techniques in Particle Physics" (Wiley-vch 2014), and I would like to offer here my impressions and thoughts on the material.
The book comes in soft cover (I am unaware if a hardcover will also be available any time soon), and is printed on nice and good-smelling acid-free paper. This might look like a detail to you, but a good part of my judgement about a book comes from the way it smells ;-). The book costs $89 at WILEY, and you can get a good preview of the material and sample chapters at this site.
The cover shows a CMS heavy-ion event display overlaid to a few typical graphs of multivariate techniques. I should mention that the subtitle reads "Fits, Density Estimation and Supervised Learning". Indeed, the book is geared toward multivariate techniques in data analysis, and cannot be mistaken for a general-purpose book on statistical techniques; despite that, the authors have made an effort to insert in the first two chapters (ch.2 and ch.3, as the first is an introduction) some reminder of the most important techniques. Of course one cannot imagine that this is more than a quick reminder aimed at readers who already know the topics dealt with there: goodness-of-fit tests, which are the main subject of chapter 3, are done with in 15 pages; confidence intervals, in chapter 2, occupy even a few less.
The main part of the book is a discussion of the many multivariate techniques that exist for advanced data analysis, with a few examples taken from particle physics and astrophysics. Rather than trying to be a deep treatise (there exist others on the market), the book deals with every topic at a level suitable to anybody who is only generically familiar with statistical tools and who wants to learn the basics of methods which most of us have not even ever heard about. For good or for bad, these methods have become extremely important in basic science once computing power has surpassed the required level to easily handle them.
Every chapter is complemented with a few exercises and a selected list of references. I am not a big fan of books that give you work assignments without offering a solution at the back, or at least some trace of the solution; I hope authors will make an effort to provide worked out solutions to at least a sample of the exercises in their site. That would be a great addition to the material they offer.
All in all, I believe this is a very useful book for researchers who wish to learn more about the techniques that have become available in the course of the last 20 years to achieve more powerful inference from their data. Not knowing what are kernel estimation, bootstrap, or random forests has become increasingly embarassing if you work in the field.
- PHYSICAL SCIENCES
- EARTH SCIENCES
- LIFE SCIENCES
- SOCIAL SCIENCES
Subscribe to the newsletter
Stay in touch with the scientific world!
Know Science And Want To Write?
- Lettuces Now, What Next - Could Astronauts Get All Their Oxygen And Food From Algae Or Plants?
- Artificial Intelligence: It's Time To Talk About What Emotions We Want AI To Have
- Brain Size Matters When It Comes To Remembering
- Most Idiotic Rejection Of Course From Philosopher Of Science Not Grasping Relativity
- Innate GMO Potato Deregulated By USDA
- An Historical Moment For Diabetes
- Will You Murder Your Wife?
- "The top spin is indeed being measured, with results in agreement with standard model predictions..."
- "Without a magnetic field on Mars, it should be patently obvious that terraforming attempts would..."
- "For instance would it be possible to measure the g-factor of the top quark? A dirac particle should..."
- "Dr. Federoff is wrong about golden rice being tied up in the regulatory process for more than a..."
- "Turbine operators have an inate drive to reduce all kinds of noise in their turbines - noise is..."
- Fish oil diet versus gut microbes
- Naps linked to reduced blood pressure and fewer medications
- Why girls are less interested in computer science: Classrooms are too 'geeky'
- Frogs make irrational choices - and what means for understanding animal mating
- Depression, blood pressure extremes predict highest rates of vascular events