Statistical Evaluations in Exploration for Mineral Deposits
(Sprache: Englisch)
Statistical evaluations of exploration data are the basis for decisions to be made at various stages of an exploration project. In contrast to other geostatistical books, Statistical Evaluations in Exploration for Mineral Deposits focuses...
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Klappentext zu „Statistical Evaluations in Exploration for Mineral Deposits “
Statistical evaluations of exploration data are the basis for decisions to be made at various stages of an exploration project. In contrast to other geostatistical books, Statistical Evaluations in Exploration for Mineral Deposits focuses not only on theory, but examples are also given, frequently originating from experience in mineral exploration by the author who worked worldwide for a mining company. Together with its companion volume, Economic Evaluations in Exploration, the book illustrates methods used in exploration campaigns and mining activities. It is intended as a vademecum for geologists who are forced to make quick decisions regarding an exploration project. It also addresses scientists and students involved in teaching or in mineral economic evaluations, recommendations or decisions.
Inhaltsverzeichnis zu „Statistical Evaluations in Exploration for Mineral Deposits “
Preface.- The Most Important Notations and Abbreviations.- 1 Introduction to Some Fundamental Statistical Concepts.- 1.1 General Definitions.- 1.2 Frequency Distribution.- A Mineral Deposit Statistics.- 2 Treatment of the Data Set.- 2.1 A Simple Case of Calculating a Frequency Distribution.- 2.2 Using Class Intervals for Calculating Frequency Distributions.- 2.3 Frequency Distribution of Samples with Dissimilar Specifications.- 3 Mean, Variance and Standard Deviation.- 3.1 The Mean.- 3.1.1 The Mean of Equal-Weighted Values.- 3.1.2 The Mean of Unequally-Weighted Values.- 3.1.3 The Mean of Data Within Class Intervals.- 3.2 Variance and Standard Deviation of Sample Size and Population.- 3.2.1 Calculation for Equivalent Samples.- 3.2.2 Determination of the Variance and Standard Deviation for Non-Equivalent or Categorized Values.- 3.2.2.1 Graphical Determination of the Variance and Standard Deviation.- 3.2.2.2 Calculation of Variance and Standard Deviation of Non-Equivalent or Categorized Values.- 3.3 Coefficient of Variation.- 3.4 Other Parameters (Median, Mode Value).- 4 The Normal Distribution.- 5 Testing the Normal Distribution Hypothesis.- 5.1 Graphical Test.- 5.1.1 Calculation of the Cumulative Frequency.- 5.1.2 Cumulative Frequency Function of the Normal Distribution and the Derivation of the Probability Grid.- 5.1.3 Plotting the Cumulative Frequency Values of a Real Distribution on the Probability Grid.- 5.2 Chi-Square Test.- 6 Standard Deviation and Variance of the Mean.- 6.1 Calculation of the Standard Case.- 6.2 Weighting Different Variances of the Mean.- 7 Estimation of the Error.- 7.1 Confidence Intervals of a Mean Value.- 7.2 The Average Error.- 7.3 The Law of Perpetuation of Errors.- 8 Skewed Distributions.- 8.1 Introduction.- 8.2 Measurement of Skewness.- 8.3 Assessing Isolated or only a Few High Values.- 8.3.1 Corrections Using the Graphical Cumulative Frequency.- 8.3.2 Reducing the Highest Values to the Next-Highest.- 8.3.3 Statistical Outlier Tests.-
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8.3.3.1 Test for an Extensive Data Set.- 8.3.3.2 Test for a Restricted Data Set.- 8.3.3.3 The FUNOP Method.- 8.4 Practical Experience with the Cut Levels.- 8.4.1 Experience from the Gold Sector.- 8.4.2 Derivation of the Cut Level from the Lognormal Distribution.- 9 The Use of the Lognormal Distribution.- 9.1 Introduction.- 9.2 The Lognormal Distribution (for Numerous High Values).- 9.2.1 Derivation of the Lognormal Distribution.- 9.2.2 The Logarithmic Probability Grid.- 9.2.3 Determination of Parameters for the Lognormal Distribution.- 9.2.3.1 Mean and Variance.- 9.2.3.2 The Correction Factor ?.- 9.2.3.2.1 Graphical Determination of the Correction Factor ?.- 9.2.3.2.2 Mathematical Determination of the Correction Factor ?.- 9.2.3.2.3 Using a-Priori Information for the Estimation of the Correction Factor ?.- 9.3 Determination of the Arithmetic Mean Value for Skewed Sample Distributions.- 9.3.1 Introduction.- 9.3.2 Determination of the Arithmetic Mean from the Logarithmic Mean and Logarithmic Variance.- 9.3.3 Sichel's - Estimator.- 9.3.4 Finney's Diagram.- 9.3.5 Confidence Interval of the Arithmetic Mean of Lognormally Distributed Data.- 9.3.6 Statistical Treatment of outlier Data Using Two Lognormally Distributed Data.- 10 Other Distributions for the Evaluation of Mineral Deposit Data.- 11 Statistical Problems Encountered in Sampling and the Analytical Results.- 11.1 Sample Collection.- 11.1.1 General Remarks.- 11.1.2 Sample Size.- 11.1.2.1 Introduction.- 11.1.2.2 Gy's Sampling Formula.- 11.1.2.3 Estimation of the Sample Size for a Known Standard Deviation s.- 11.1.2.3.1 Formula for Estimating the Sample Size.- 11.1.2.3.2 Estimation of the Standard Deviation for Two Samples from Each Component.- 11.1.2.3.3 Estimation of the Standard Deviation for Three or More Samples from Each Component.- 11.1.3 The Special Case of Gold.- 11.2 Check Analyses.- 11.2.1 Discussion of the Problem.- 11.2.2 Mathematical Comparison of Two Series of Analyses Using the Student's t-Factors.
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Autoren-Porträt von Friedrich-Wilhelm Wellmer
In the course of the exploration of mineral deposits and mining activities, abundant data are gathered that need statistical treatment for the evaluation of the economical success of the project. Together with the companion volume, Economic Evaluations in Exploration, this book offers a complete survey of methods, illustrated by practical examples.
Bibliographische Angaben
- Autor: Friedrich-Wilhelm Wellmer
- 2011, Softcover reprint of the original 1st ed. 1998, 379 Seiten, Maße: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Übersetzer: D. Large
- Verlag: Springer, Berlin
- ISBN-10: 3642643256
- ISBN-13: 9783642643255
Sprache:
Englisch
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