Course Introduction

Practical Geostatistics 2000 - 1: Classical Statistics

Version: 28 February 2007

Isobel Clark William Harper

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Introduction

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

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 x² 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

• Relationships

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.

Learning Outcomes

Participants who successfully complete this course and the certification requirements will be able to perform the following.

• Understand and apply the basic descriptive and graphical tools of statistics including measures of central tendency, measures of spread and variability, histograms, bar charts and box plots.

• Understand and apply the Normal probability distribution and its parameters and properties including mean, standard deviation, confidence intervals and selection calculations.

• Understand and apply the Lognormal probability distribution and its parameters and properties including mean, standard deviation, confidence intervals and selection calculations.

• Understand and apply discrete probability distributions including Binomial, Poisson, geometric and mixed distributions.

• Understand and apply the principles of hypothesis testing including single sample tests, two sample tests and paired tests.

• Understand and apply the principles of data relationships including straight line, multi-variable and curved relationships, and polynomial trend surface analysis.

Course Requirements

Basic requirements for successful completion of this course include the following.

• Familiarity with algebra, simple calculus and basic statistics.

Course Certification

This course qualifies for EduMine Certification. A certificate will be issued to an EduMine enrollee who registers for certification and successfully completes the certification requirements. The total certification fee for this course is Can$285.

2.5 CEUs  (Continuing Education Units) will be awarded for successful completion of certification requirements for this course. EduMine meets the Criteria for Certification established by the Authorized Provider Commission of The International Association for Continuing Education and Training, 1620 Eye Street, N.W., Suite 615, Washington, DC 20006.

To register for certification for this course use the "Course Certification Entry or Registration" link above or below on the right.

UBC Certificate in Mining Studies

This course qualifies as online learning for the University of British Columbia - Certificate in Mining Studies in the Mining Methods and Mine Planning stream. Students who complete the certification requirements for this course may optionally register for the Certificate in Mining Studies program and complete the associated classroom component. For further information click UBC Certificate in Mining Studies

[Note: Participation in the UBC Certificate in Mining Studies program is optional. For EduMine certification proceed as described under Course Certification above.]

Start the Course with an Orientation Session	Review the Course at the Summary Level	Start the Course at the Detailed Text Level	Course Certification Entry or Registration
(first time viewers)	(reviewers)	(serious viewers)	(certification)