Practical Geostatistics 2000 -1: Classical Statistics
Practical Geostatistics 2000 - 1: Classical Statistics is the first of a set of two courses. The companion course is Practical Geostatistics 2000 - 2: Spatial Statistics.
Dr. Isobel Clark BSc MSc DIC PhD FSS FSAIMM FIMM CEng and William Harper PhD, PE
Published by EduMine
Training Time: 25 hours approximate
SME Course Completion Certificate available
EduMine CEU Certification available upon request with minimum review score of 75%.
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These courses are based on 28 years of teaching statistics and geostatistics to mining engineers, geologists, hydrologists, soil scientists, climatologists, plus the occasional geographer, pattern recognition expert, meteorologist, statistician, and computer scientist. Even, on one occasion, an accountant. Over those years, we have endeavoured to pare away all extraneous mathematics and concentrate on intuitive derivations where possible.
Readers interested in rigorous mathematical proofs are urged to stop here and turn to the more theoretically based material (a comprehensive bibliography is included). This course is not intended to turn out fully-fledged geostatisticians. It is intended for people with problems to be solved which can be assisted by a geostatistical approach.
To benefit from this course you need to be fairly comfortable with basic algebra. That is, with the notion of using symbols as shorthand for longer statements. We have worked hard to bring you consistent notation throughout the course. Where notation is out of our control, we explain carefully what each symbol stands for and try not to use that symbol for anything else.
Calculus—differentiation and integration—is discussed at various points in the text. The reader is not expected to do any calculus (as such) but is expected to know that the differential of x squared is 2x. The only other complication is the frequent use of simultaneous equations. We tend not to use matrix algebra in this course but will give the matrix form after explanations have been given in simple algebra. For example, linear regression is easier to understand if developed with algebra, but very simple to implement in spreadsheets if matrices are used.
If we haven't scared you off yet, be reassured by the fact that all the analyses are illustrated with real data sets in full worked examples.
Data sets and software can be downloaded from Ecosse Geostatistics. There are also exercises for you to try. Answers are available for you to check your results. Most of these exercises have been collected and used in classes or examinations at Final (Senior) Year and Master's levels.
It is our own fundamental regret that this course cannot contain the jokes, anecdotes and sheer fun that we have giving the course in person. We do advise you, however, to keep your sense of humour and common sense at all times while taking this course.The principal topics covered by this course include:
- Why a Statistical Approach?
- The Normal (Gaussian) Distribution
- The Lognormal Distribution (and Variants)
- Discrete Statistics
- Testing Hypotheses
The course comprises 24 viewing sessions, each of approximately 60 minutes duration, plus supporting figures, tables, worked examples, references and appendices, and interactive reviews that confirm your achievement of the learning objectives.
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