Course Title: Sampling and Quality Control

Part A: Course Overview

Course Title: Sampling and Quality Control

Credit Points: 12.00


Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

MATH2205

City Campus

Undergraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

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

MATH2205

City Campus

Undergraduate

171H School of Science

Face-to-Face

Sem 2 2017

Course Coordinator: Mali Abdollahian

Course Coordinator Phone: +61 3 9925 2248

Course Coordinator Email: mali.abdollahian@rmit.edu.au

Course Coordinator Location: 8.9.82


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. Extensive use is made of various statistical computing software to analyse and evaluate the performance of services.


Objectives/Learning Outcomes/Capability Development

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

Knowledge and technical competence

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

Problem-solving

  • 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.

Communication

  • 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.


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. Explain the concepts of Statistical Quality Control, Quality Assurance and Performance Analysis and associated techniques.
  3. Construct appropriate Quality Control Charts / Forecasting models and argue the role of such charts / models in monitoring a process.
  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

A 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.

A Library Guide is available at:

http://rmit.libguides.com/mathstats


Overview of Assessment

Assessment Tasks:

Early Assessment Task: Assignment 1

Weighting 5%

This assessment task supports CLOs 1             

 

Assessment Task 2: Assignment 2

Weighting 20%

This assessment task supports CLOs 1, 2, 3

 

Assessment Task 3: Assignment 3

Weighting 25%

This assessment task supports CLO 1, 2, 3

 

Final Exam

Weighting 50% 

This assessment task supports CLO 1, 2, 3, 4, 5