Chi-Squared Data Analysis and Model Testing for Beginners

by Carey Witkov, Keith Zengel

Overview

Recent groundbreaking discoveries in physics have relied on chi-squared analysis and model testing. This is the first book to make this data analysis method accessible to students in introductory physics lab courses and others who need to learn this method, such as beginning researchers in astrophysics and beginners in data science.

Product Details

ISBN-13:	9780198847144
Publisher:	Oxford University Press
Publication date:	11/17/2019
Pages:	112
Product dimensions:	9.30(w) x 6.20(h) x 0.50(d)

About the Author

Carey Witkov, Preceptor in Physics, Harvard University, Massachusetts,Keith Zengel, Preceptor in Physics, Harvard University, Massachusetts

Carey Witkov, PhD, is a preceptor in physics at Harvard University with over 40 years of undergraduate physics teaching experience. He teaches Harvard University's innovative Principles of Scientific Inquiry (PSI) introductory physics lab courses within which freshman and sophomore students learn chi-squared analysis and model testing. His favorite physics lab experiments are those that involve simple equipment but sophisticated analysis.

Keith Zengel received his PhD in experimental particle physics from Brandeis University in 2015. He worked on the ATLAS experiment at the Large Hadron Collider, searching for supersymmetric and exotic particles and writing software for the endcap muon spectrometer. Since then he has worked as a Preceptor in Physics at Harvard University. His current research interests are introductory and intermediate classical mechanics, electrodynamics, and data analysis.

Table of Contents

1. Introduction2. Statistical Toolkit3. One Parameter Chi-squared Analysis4. Two Parameter Chi-Squared Analysis5. Case Study 1: Falling Chains6. Case Study 2: Modeling Air Resistance on Falling Coffee Filters7. Advanced Topics

Editorial Reviews

"...delightful little book with a simple aim - to make chi-squared data analysis accessible to first-year physics students. Not only does the book succeed in this aim, but it does so without resorting to the oftused "collection of recipes" approach that makes statistical modeling seem more like magic than a coherent system of scientific thinking...I highly recommend this book for many applied fields - not just physics." — Thomas J. Faulkenberry, Mathematical Association of America, Mathematical Association of America website

From the Publisher