000			02113 a2200205 4500
005			20250416161256.0
008			240425b2017|||||||| |||| 00| 0 eng d
020			_a9781107096004
041			_aEnglish
082			_a519.50285 C43
100			_aChave, Alan D. _eAuthor _93866
245			_aComputational statistics in the earth sciences: with applications in MATLAB
260			_bCambridge University Press, _c2017. _aUK:
300			_axiii, 451p.; 23cms.
500			_aBased on a course taught by the author, this book combines the theoretical underpinnings of statistics with the practical analysis of Earth sciences data using MATLAB. The book is organized to introduce the underlying concepts, and then extends these to the data, covering methods that are most applicable to Earth sciences. Topics include classical parametric estimation and hypothesis testing, and more advanced least squares-based, nonparametric, and resampling estimators. Multivariate data analysis, not often encountered in introductory texts, is presented later in the book, and compositional data is treated at the end. Datasets and bespoke MATLAB scripts used in the book are available online, as well as additional datasets and suggested questions for use by instructors. Aimed at entering graduate students and practicing researchers in the Earth and ocean sciences, this book is ideal for those who want to learn how to analyse data using MATLAB in a statistically-rigorous manner. MATLAB examples, including scripts, are integrated with the underlying theory throughout the book, facilitating a 'learning by example' approach for those who are not mathematically inclined, and reinforcing concepts for those who are Exemplar data are taken from the Earth and ocean sciences, to make the examples more familiar to readers The new field of compositional data that pervades the Earth sciences is covered in the final chapter
650			_aEarth sciences _xStatistical methods _93867
650			_aEarth sciences-statistical methods _xData processing _93868
650			_aMathematical statistics _xData processing _92281
942			_cBK
999			_c1125 _d1125