Authorised by Academic Registrar, April 1996
Objectives Statistics section Students will be able to demonstrate an understanding of basic principles of good experimental design; use numerical or graphical techniques, as appropriate, to summarise data; formulate simple probabilistic models and calculate relevant probabilities (including reliabilities) as part of a problem solution; make simple inferences from sample data based on point and interval estimation of population means, differences between means, main effects and interactions in 2k factorial experiments and simple linear regression parameters; use a statistical package and/or statistical calculator for the above tasks. Operations research section Students will be able to formulate linear programming models of resource constrained problems and obtain optimal solution using graphical and/or mathematical methods; perform simple post-optimality analysis on profit (cost) coefficients and resources; identify a range of network models and apply relevant solution techniques; specify and apply non-probabilistic and probabilistic choice criteria in making decisions; calculate and apply the optimal EOQ decision rule in the classical situation, with quantity discount and for simple production runs; describe some basic queueing systems and apply simulation analysis to some of the problems; use a decision making system and/or a calculator for the above tasks.
Synopsis This subject is designed to provide students with a range of techniques for making considered decisions. Students will be required to demonstrate competence in a spectrum of procedures for quantitative analysis of resource management problems, including the use of computer packages where appropriate. Section A - The nature of statistics: basic concepts of experimental design; collecting and organising data; use of the statistical package MINITAB; review of probability models and applications such as statistical quality control; sampling (random sampling, implications of the central limit theorem); control charts for process mean and process variability; estimation from random samples; point and interval estimation of means and differences between means; factorial experiments with factors at two levels; regression models (introduction to applications of simple linear regression). Section B - Operations research and areas of its potential applications in engineering: linear programming (problem formulation, solution through graphical procedure and simplex method, and use of available LP packages); decision making under risk; the value and quality of information; network models including shortest-route, maximum-flow, assignment and transportation problems; analysis of inventory control models; introduction to simulation process and simple applications.
Assessment Three assignments: 40% + Examination (2 x 2 hours): 60%