Statistics for Mining Engineering

Statistics for Mining Engineering
R52NAgAAQBAJ
288
By:"Jacek M. Czaplicki"
"Mathematics"
Published on 2014-01-14 by CRC Press

M Markov chain 34, 35, 211 Markov process 22, 34, 35, 135, 227, 230 Maximum \u003cbr\u003e\nlikelihood method 113 Median, \u003cb\u003edefinition\u003c/b\u003e 12 Method of moments 112, 126, 127, \u003cbr\u003e\n131, 132 of quantiles 112 maximum likelihood 113, 126 Mode, \u003cb\u003edefinition\u003c/b\u003e 13 ...

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Many areas of mining engineering gather and use statistical information, provided by observing the actual operation of equipment, their systems, the development of mining works, surface subsidence that accompanies underground mining, displacement of rocks surrounding surface pits and underground drives and longwalls, amongst others. In addition, the actual modern machines used in surface mining are equipped with diagnostic systems that automatically trace all important machine parameters and send this information to the main producer’s computer. Such data not only provide information on the technical properties of the machine but they also have a statistical character. Furthermore, all information gathered during stand and lab investigations where parts, assemblies and whole devices are tested in order to prove their usefulness, have a stochastic character. All of these materials need to be developed statistically and, more importantly, based on these results mining engineers must make decisions whether to undertake actions, connected with the further operation of the machines, the further development of the works, etc. For these reasons, knowledge of modern statistics is necessary for mining engineers; not only as to how statistical analysis of data should be conducted and statistical synthesis should be done, but also as to understanding the results obtained and how to use them to make appropriate decisions in relation to the mining operation. This book on statistical analysis and synthesis starts with a short repetition of probability theory and also includes a special section on statistical prediction. The text is illustrated with many examples taken from mining practice; moreover the tables required to conduct statistical inference are included.

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