Course Title: Sampling and Quality Control

Part A: Course Overview

Course Title: Sampling and Quality Control

Credit Points: 12.00


Course Code




Learning Mode

Teaching Period(s)


City Campus


145H Mathematical & Geospatial Sciences


Sem 1 2010,
Sem 1 2011,
Sem 1 2012,
Sem 1 2013,
Sem 1 2014,
Sem 1 2015


City Campus


171H School of Science


Sem 2 2017,
Sem 2 2019,
Sem 2 2021

Course Coordinator: Associate Prof. Mali Abdollahian

Course Coordinator Phone: +61 3 9925 2248

Course Coordinator Email:

Course Coordinator Location: 015.04.006

Course Coordinator Availability: by email appointment

Pre-requisite Courses and Assumed Knowledge and Capabilities

MATH2200 Introduction to Probability and Statistics and MATH2201 Basic Statistical Methodologies or their equivalent.

Course Description

The course aims to provide the theoretical knowledge and skills for the applied scientist who needs to monitor and improve the quality of service or industrial processes. It focuses on concepts and various techniques used in sampling and design in the context of quality control. The course includes extensive use of various statistical computing software to analysis and evaluate the performance of services.

Objectives/Learning Outcomes/Capability Development

Program Learning Outcomes (PLOs):

This course contributes to the following Program Learning Outcomes for BP083 Bachelor of Sciences (Applied Mathematics and Statistics ), BP245 Bachelor of Sciences (Statistics) and BH119 Bachelor of Analytics (Honours) BP331 Bachelor of Analytics.

Knowledge and technical competence

  • An understanding of appropriate and relevant, fundamental and applied mathematical and statistical knowledge, methodologies and modern computational tools.


  • The ability to bring together and flexibly apply knowledge to characterise, analyse and solve a wide range of problems
  • An understanding of the balance between the complexity / accuracy of the mathematical / statistical models used and the timeliness of the delivery of the solution.


  • The ability to effectively communicate both technical and non-technical material in a range of forms (written, electronic, graphic, oral), and to tailor the style and means of communication to different audiences.  Of particular interest is the ability to explain technical material, without unnecessary jargon, to lay persons such as the general public or line managers.

Course Learning Outcomes (CLOs)

On completion of this course you should be able to:

  1. Apply sampling techniques to real world quality control problems and to both theoretical and applied research.
  2. Construct appropriate Quality Control Charts / Forecasting models and argue the role of such charts / models in monitoring a process.
  3. Explain the concepts of Statistical Quality Control, Quality Assurance and Performance Analysis and associated techniques.
  4. Assess the ability of a particular process to meet customer expectations.
  5. Develop an appropriate quality assurance plan to assess the ability of the service to meet requisite national and international quality standards.

Overview of Learning Activities

  • Lectures where underlying theory will be presented.
  • Regular computer laboratory classes that will reinforce the material covered in   lectures and in your personal study.
  • Assignments to practice the usage of software packages.

Overview of Learning Resources

List of recommended texts will be provided.

You will have access to extensive course materials made available via the online RMIT Learning Hub (myRMIT), including digitised readings, lecture notes and a detailed study program, external internet links and access to RMIT Library online and hardcopy resources.

Library Subject Guide for Mathematics & Statistics:

Overview of Assessment

This course has no hurdle requirements.

Assessment Tasks

Early Assessment Task: Sampling methods assignment
Weighting 30%
This assessment task supports CLOs 1

Assessment Task 2: Online theory assessment
Weighting 30%
This assessment task supports CLOs 1, 2, 3,

Assessment Task 3: Report
Weighting 40%
This assessment task supports CLO 1,2, 3, 4, 5