SHE Level 3
SCQF Credit Points 20.00
ECTS Credit Points 10.00
Module Code M3N109303
Module Leader n/a
School Glasgow School for Business and Society
Subject Management
  • B (January start)

Pre-Requisite Knowledge

Level 1 Module - Business Data Analysis

Summary of Content

Introduction to the statistical distributions and principles relating to sampling, average weight and the techniques of statistical quality control. Detailed treatment of the techniques of statistical quality control, their implementation, use and interpretation, and the pragmatic issues behind adoption of such methods within manufacturing organisations. The main focus is on manufacturing processes governed by Weights and Measures statutes (for example the food industry).


Discrete probability distributions, applications and approximation Normal distribution applications for trading standards (Reference Testing, Sums and Differences of Independent Random Variables)Inferential Statistics (Sampling Distributions, Estimation & Hypothesis testing for means & proportions)Tools and holistic approaches for quality improvement On-Line process control: Mean & range control charts; Control charts for attribute data; Process capability assessment; CUSUM Charts; Recommended systems under Part V; Weights & Measures Act 1985.Acceptance Sampling The testing of Automatic Weighing Machines

Learning Outcomes

On completion of this module the student should be able to:Understand the statistical principles behind the concept of average weight Apply the techniques of sampling and quality control as recommended under consumer protection statutesDevelop and appraise acceptance sampling plansApply standard tests of the operation of checkweighing machines, and interpret the resulting statistics Develop a range of standard statistical quality control charts, including mean, range and attribute control charts, cumulative sum (CUSUM) charts and operating characteristic (OC) curvesCritically appraise the above methods, and advise traders on appropriate systems for regulatory compliance

Teaching / Learning Strategy

Two hours lecture, one hour tutorial and one hour computing lab per week Students are required to prepare for tutorials in advance using www, periodicals (via electronic journal sources) and textbooks. Lab-based practical sessions provide students with an opportunity to model the various distributions and observe the implications of varying input parameters, and to generate statistical quality control charts from raw data. Student-centred activities include; seminars, group work, use of CIT and case study analysis.

Indicative Reading

Besterfield, Dale.H., (1994). Quality Control 4th Ed., Prentice-Hall Bissell, Derek. (1994), Statistical Methods for SPC and TQM, Chapman & Hall Hubbard, Merton. R. (1996), Statistical Quality Control for the Food Industry, Chapman & Hall (USA)Murdoch J. & Barnes J.A. (2000), Statistical tables for Science, Engineering, Management & Business Studies, 3rd Ed, MacMillanOakland, John. S. (1999), Statistical process control (4nd Ed.), Butterworth-Heinmann. Price, Frank, Right first time, GowerJournals, Sources and ReferencesThe British Food Journal Food Monitor Food ControlJournal of Applied StatisticsTrading Standards Microfile

Transferrable Skills

Numeracy and quantitative skills; problem solving and decision making; report writing, information retrieval from electronic sources, use of CIT for business applications; software skills (programming and statistical functions in Excel).

Module Structure

Activity Total Hours
n/a 20.00
n/a 2.00
Lectures (FT) 24.00
Practicals (FT) 12.00
Seminars (FT) 12.00
Assessment (FT) 20.00
Independent Learning (FT) 90.00

Assessment Methods

Component Duration Weighting Threshold Description
Coursework 0.00 25.00 35% Analysis and report based upon case study data
Coursework 0.00 25.00 35% Analysis and report based upon case study data
Exam (Exams Office) 2.00 50.00 35% Examination