01507    a2200361   4500001001100000005001700011008003900028020001800067037003600085040000700121041000800128072001500136072001600151072001400167072001300181072001400194072001200208072002100220072002100241072002100262072002100283072002200304100002300326245009900349250000600448260002400454300001000478520056400488700002801052700002701080700002301107999001501130036778028320250317100417.0250312042021xx                   eng    a9780367780289  bTaylor & FranciscGBP 45.99fBB  a01  aeng7 aTGM2thema7 aPHFC2thema7 aPB2thema7 aTGM2bic7 aPHFC2bic7 aPB2bic7 aSCI0770002bisac7 aMAT0290002bisac7 aSCI0550002bisac7 aTEC0210002bisac7 a620.1107272bisac1 aJeffrey P. Simmons10aStatistical Methods for Materials SciencebThe Data Science of Microstructure Characterization  a1  bCRC Pressc20210331  a514 p  bData analytics has become an integral part of materials science. This book provides the practical tools and fundamentals needed for researchers in materials science to understand how to analyze large datasets using statistical methods, especially inverse methods applied to microstructure characterization. It contains valuable guidance on essential topics such as denoising and data modeling. Additionally, the analysis and applications section addresses compressed sensing methods, stochastic models, extreme estimation, and approaches to pattern detection.1 aLawrence F. Drummy4B011 aCharles A. Bouman4B011 aMarc De Graef4B01  c3001d3001