C&ENVENG 7064 - Non-Stationarity, Selection & Recoverability

North Terrace Campus - Winter - 2017

There are two major components in this course. (1) Non-stationarity: Introduction to the concept of drift (trend) by way of geological examples. Definitions of the various forms of stationarity (in a statistical sense). Simple ways of dealing with non-stationary variables. Detailed case study to illustrate the assessment and quantification of non-stationarity. Universal kriging and universal kriging variances. Intrinsic Random Functions and generalised covariances. Statistical tests for constant mean of a spatial variable - the D-statistic and the global D-statistic. (2) Selection & Recoverability: This component is essentially a study of scale effects. The applications are to mineral resources and environmental contamination (ground) but, depending on the chosen specialisations, can be expanded to all other applications. The emphasis is on conceptual approaches to simple applications leading to simple spatial statistical methods to predict the effects of changing scale - e.g. predicting the distributions of grade values of large blocks from the grade values of sample volumes. The information effect and the support effect - concepts, quantification and practical consequences. Parametric formulation of the change of scale. The affine correction. Local and global corrections for scale effects.

  • General Course Information
    Course Details
    Course Code C&ENVENG 7064
    Course Non-Stationarity, Selection & Recoverability
    Coordinating Unit School of Civil, Environmental & Mining Eng
    Term Winter
    Level Postgraduate Coursework
    Location/s North Terrace Campus
    Units 3
    Contact Block teaching, 9-5, Mon-Fri, one week only
    Available for Study Abroad and Exchange N
    Assumed Knowledge C&ENVENG 7043, C&ENVENG 7056 & STATS 7061
    Restrictions Available to M Geostatistic students only
    Course Description There are two major components in this course.
    (1) Non-stationarity: Introduction to the concept of drift (trend) by way of geological examples. Definitions of the various forms of stationarity (in a statistical sense). Simple ways of dealing with non-stationary variables. Detailed case study to illustrate the assessment and quantification of non-stationarity. Universal kriging and universal kriging variances. Intrinsic Random Functions and generalised covariances. Statistical tests for constant mean of a spatial variable - the D-statistic and the global D-statistic.
    (2) Selection & Recoverability: This component is essentially a study of scale effects. The applications are to mineral resources and environmental contamination (ground) but, depending on the chosen specialisations, can be expanded to all other applications. The emphasis is on conceptual approaches to simple applications leading to simple spatial statistical methods to predict the effects of changing scale - e.g. predicting the distributions of grade values of large blocks from the grade values of sample volumes. The information effect and the support effect - concepts, quantification and practical consequences. Parametric formulation of the change of scale. The affine correction. Local and global corrections for scale effects.
    Course Staff

    Course Coordinator: Professor Peter Dowd

    Course Timetable

    The full timetable of all activities for this course can be accessed from Course Planner.

    The course runs in intensive mode 9-5pm each day for one week with a mixture of tutorials and lectures. An hour break is provided for lunch. Assignments are to be completed in remaining time outside contact hours.
  • Learning Outcomes
    Course Learning Outcomes

    On successful completion of this course students will:

    1. have a detailed understanding of the forms and consequences of non-stationarity and under what circumstances it must be accommodated in practical applications,

    2. an ability to apply universal kriging in detail to tutorial examples and, by way of a computer program, to practical data sets, and

    3. an understanding of the principles of intrinsic random functions and an ability to use generalised covariances as an automatic means of filtering drift in estimations.

    4. have an understanding of scale effects as they apply to spatial variables and will be able to apply simple methods to predict the statistical characteristics of a variable on a scale larger than the scale on which the data for the variable have been measured.

    University Graduate Attributes

    This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:

    University Graduate Attribute Course Learning Outcome(s)
    Critical thinking and problem solving
    • steeped in research methods and rigor
    • based on empirical evidence and the scientific approach to knowledge development
    • demonstrated through appropriate and relevant assessment
    1,2,3,4
  • Learning Resources
    Required Resources
    Lecture notes are required reading for this course.
  • Learning & Teaching Activities
    Learning & Teaching Modes
    Delivery is intensive mode, involving: lectures, tutorials and examples classes.
    Workload

    The information below is provided as a guide to assist students in engaging appropriately with the course requirements.

    A standard 3 unit load is 156 hours. 35 hours are allocated for lectures and tutorials. Approximately 120 hours are allocated to completing assignments and revising for the exam.
    Learning Activities Summary

    No information currently available.

  • Assessment

    The University's policy on Assessment for Coursework Programs is based on the following four principles:

    1. Assessment must encourage and reinforce learning.
    2. Assessment must enable robust and fair judgements about student performance.
    3. Assessment practices must be fair and equitable to students and give them the opportunity to demonstrate what they have learned.
    4. Assessment must maintain academic standards.

    Assessment Summary
    50% coursework and 50% formal, written examination.
    Assessment Detail

    No information currently available.

    Submission

    No information currently available.

    Course Grading

    Grades for your performance in this course will be awarded in accordance with the following scheme:

    M10 (Coursework Mark Scheme)
    Grade Mark Description
    FNS   Fail No Submission
    F 1-49 Fail
    P 50-64 Pass
    C 65-74 Credit
    D 75-84 Distinction
    HD 85-100 High Distinction
    CN   Continuing
    NFE   No Formal Examination
    RP   Result Pending

    Further details of the grades/results can be obtained from Examinations.

    Grade Descriptors are available which provide a general guide to the standard of work that is expected at each grade level. More information at Assessment for Coursework Programs.

    Final results for this course will be made available through Access Adelaide.

  • Student Feedback

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    SELTs are an important source of information to inform individual teaching practice, decisions about teaching duties, and course and program curriculum design. They enable the University to assess how effectively its learning environments and teaching practices facilitate student engagement and learning outcomes. Under the current SELT Policy (http://www.adelaide.edu.au/policies/101/) course SELTs are mandated and must be conducted at the conclusion of each term/semester/trimester for every course offering. Feedback on issues raised through course SELT surveys is made available to enrolled students through various resources (e.g. MyUni). In addition aggregated course SELT data is available.

  • Student Support
  • Policies & Guidelines
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