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Title:
Statistics for mining engineering
Personal Author:
Publication Information:
Boca Raton : CRC Press/Balkema is an imprint of the Taylor & Francis Group, an informa business, 2014
Physical Description:
xiii, 274 pages : illustrations ; 26 cm.
ISBN:
9781138001138
Abstract:
"Knowledge about modern statistics is necessary for mining engineers; not only on how statistical analysis of data should be conducted and statistical synthesis should be done, but also on understanding the results obtained and how to use them to make appropriate decisions connected with a mining operation. This book on statistical analysis and synthesis is preceded by a short repetition of the probability theory. A special section about statistical prediction is also included. The text is illustrated by many examples taken from mine practice, moreover the tables required to conduct statistical inference are attached"--provided by publisher

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30000010335987 TN272.7 C93 2014 Open Access Book Book
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Summary

Summary

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.


Author Notes

Jacek M. Czaplicki (Mining Mechanization Institute, Silesian University of Technology, Gliwice, Poland) has been an academic lecturer for forty years and is continuously associated with his home University. He did, however, leave his school for a couple of years' lecturing in African universities.

He worked for three years at the School of Mines of the Kwara State College of Technology, Ilorin, Nigeria on a UNESCO project. A few years later, he was appointed to Zambia Consolidated Copper Mines Ltd for three years and worked as a lecturer at the School of Mines of the University of Zambia, Lusaka as part of a World Bank project.

Jacek Czaplicki received a Master of Science in Mine Mechanization from the Silesian University of Technology, Gliwice, Poland. He also obtained a Doctorate degree in Technical Sciences. Later, he submitted a dissertation and passed all of the requirements and was awarded a D.Sc. degree in Mining and Geological Engineering with a specialisation in Mine Machinery at the same home University. Currently, he is a Professor of Mining Engineering.

He has published about a hundred and forty papers and ten books in Poland and abroad. His specialization comprises mine transport, the reliability and computation of mine machinery systems and the reliability of hoist head ropes. In his research, he applies methods and models from mathematical statistics. He is an internationally recognized specialist in mine mechanization.


Table of Contents

Fundamentals
Some areas of application of mathematical statistics in mining
Analysis of data
Synthesis of data
Relationships between random variables
Synthesis of data - Regression analysis
Special topic: Prediction
Supplement - definitions of basic terms
Statistical tables
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