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Module

CEG1716 : Geospatial Mathematics and Statistics

  • Offered for Year: 2020/21
  • Module Leader(s): Dr Andrew Duncan
  • Lecturer: Dr Paul Bushby, Dr Aamir Khan
  • Owning School: Engineering
  • Teaching Location: Newcastle City Campus
Semesters
Semester 1 Credit Value: 20
Semester 2 Credit Value: 10
ECTS Credits: 15.0

Aims

An appreciation of the basic quantitative and statistical methodologies which underpin Geospatial Engineering.
To present and describe the mathematical concepts which are essential for a better understanding of various aspects of geospatial engineering, many of which rely upon, or develop from, a mathematical background.

Outline Of Syllabus

Introduction to statistics and associated mathematical tools: Summary: Elementary differentiation. Partial differentiation. Integration, Partial differentiation, Series expansions & linearisation. Stationary points of functions of two variables. Statistics of a data set, mean, standard derivation, median, median absolute deviation, mode; Summary statistics of bivariate data, correlation; Probability Density Functions; Mean and standard deviation of populations described by probability density functions; Errors in geospatial data. Normal distribution, Standard form and use of tables with applications to geomatics, Standard Error and Confidence Intervals. Hypothesis testing. t, F, chi-square tests. Vectors, Introduction to vector calculus, Introduction to matrices. Matrix algebra. Determinants, Inverse via the adjoint., Eigenvalues & Eigenvectors, Rotation matrices, Spherical coordinates. Laplace’s equation and gravity. Linear regression. Set theory & Boolean algebra, Truth tables.

Teaching Methods

Module leaders are revising this content in light of the Covid 19 restrictions.
Revised and approved detail information will be available by 17 August.

Assessment Methods

Module leaders are revising this content in light of the Covid 19 restrictions.
Revised and approved detail information will be available by 17 August.

Reading Lists

Timetable