TY - JOUR
T1 - Statistics for Mining Engineering
JF - Quarterly Journal of Engineering Geology and Hydrogeology
JO - Quarterly Journal of Engineering Geology and Hydrogeology
SP - 74
LP - 75
DO - 10.1144/qjegh2014-096
VL - 48
IS - 1
A2 - ,
Y1 - 2015/02/01
UR - https://qjegh.lyellcollection.org/content/48/1/74.abstract
N2 - Statistics for Mining Engineering. Jacek M. Czaplicki CRC Press/Balkema, Leiden, 2014, hardback/eBook, 274 pp., ISBN: 978-1-138-00113-8, £82.00 (hardback) or $129.95 (hardback or e-book).The author of this book earned a Master of Science degree in Mine Mechanization and a Doctor of Science degree in Mining and Geological Engineering with a specialization in Mine Machinery from the Silesian University of Technology, Gliwice, Poland. His areas of specialization include mine transport, reliability of mine machinery systems, and reliability of hoist head ropes. The preface acknowledges that a wide variety of technical devices are available to realize specific objectives, and that commonly several devices are linked, creating systems of devices to carry out complex functions that, in mining engineering, include excavating rock, hauling broken material, dumping waste, storing ore, and treating ore with mechanical, chemical or thermal processes.Basic knowledge of probability theory and some idea of the theory of reliability and of operation (also called exploitation in this book) are presumed. The book has nine chapters, with nine pages of references and a two-page subject index. The last two chapters are a four-page ‘explanation of some important terms’ and a 29-page collection of 18 statistical tables.Chapter 1, on fundamentals (48 pages, three sections), describes the goal and task of statistics, and provides basic terms of probability theory statistical inference. Readers who are intimidated by statistics and probability will find this book to be challenging to more or less the same degree. Readers will find the guidance and applications to be helpful. For example, the mathematical use of a ‘sample’ of a ‘general population’ is put into context by the practical decision to take only a sample because (1) testing all elements of a nearly infinite population is not possible, (2) collecting samples may be destructive and it would be senseless to destroy the whole population, (3) testing large numbers of samples has high cost, and (4) testing many samples is not …
ER -