Course Title: Quality Control and Forecasting

Part A: Course Overview

Course Title: Quality Control and Forecasting

Credit Points: 12.00


Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

MATH2149

City Campus

Undergraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

 Sem 1 2006,
Sem 1 2007,
Sem 1 2008,
Sem 1 2009

Course Coordinator: Mali Abdollahian

Course Coordinator Phone: +61 3 99252248

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

Course Coordinator Location: building 8 level 9 room 82


Pre-requisite Courses and Assumed Knowledge and Capabilities

Basic statistics course or Math 1276


Course Description

Quality Control and Forecasting is an introductory Statistical Quality Control and Time Series Modelling course for third year undergraduate students. The course provides important knowledge and skills for the applied scientist. Extensive use is made of MINITAB/ITSM200 Statistical Computing Software.


Objectives/Learning Outcomes/Capability Development

The course aims to provide the theoretical foundations that any scientist will require if they are to ensure the quality of manufactured product meets community and regulatory requirements. The course will focus on developing your abilities in critical analysis and decision making as well as teamwork and reflection. The course is an introductory level course. The theory component of the course, which gives the theory of Statistical Quality Control and Time Series Analysis, will be used in other third year and post graduate statistics courses where experimental results are either statistically controlled or are modelled for future forecasting.
The capabilities in Quality Control and Forecasting are further developed in Quality and Productivity in Industry, Time Series and Forecasting courses in the program ‘ Master by coursework in Statistics’.

Students will gain or improve capabilities in:

  • Critical Analysis and Problem Solving.
    Ability to apply scientific principles and methods to diagnose and solve problems and improve performance in simple and discrete to complex and ill-defined problems associated with the industrail production proces and environmental/ health area.
    Ability to know what questions to ask, who to ask and how to ask them.
  • Teamwork & Leadership.
    Ability to actively engage with and influence, a range of people within an organisation for mutual benefit and to accommodate alternative views.
  • Communication and Presentation.
    Ability to communicate in a range of forms (written, electronic, graphic, oral) and to tailor the style and means of communication to the circumstances of the situation and capabilities and sensitivities of the audience.
    Ability to constructively give and receive feedback .
  • Self management.
    Ability to take personal responsibility for decisions and actions while being aware of limits of knowledge and skill and when to seek help.



On successful completion of this course students will be able to:

  • Understand the techniques of Time Series and the concepts of Statistical Quality Control.
  • Construct appropriate Quality Control charts / Forecasting models and understand the role of such charts / models in monitoring a process / time series data analysis.


Overview of Learning Activities

  • Attendance at  lectures where the underlying theory will be presented
  • A weekly computer laboratory class will reinforce the material covered in lectures and in your personal study. The computer lab class is designed to assist understanding and to provide two-way feedback.
  • Shortcomings in your basic skills, e.g. selecting the appropriate quality control chart or time series model, will be revealed and your capacity to solve routine industrial problems will be assessed. Abilities to think critically and analytically will be addressed in more challenging (non routine) problems.
  • You are encouraged to discuss the given laboratory problems with others and to seek help from, and interact with, the practice class tutors.


Overview of Learning Resources

You will be able to access course information and learning materials through the Learning Hub (also known as online@RMIT) and will be provided with copies of additional materials in class. Lists of relevant reference texts and resources will be provided. You will also use computer laboratory equipment and computer software within the School during project and assignment work.


Overview of Assessment

The assessment for this course consists of weekly problems from the text book and two computer assignments. Written assignments and the practice classes will be used to provide feedback on your progress in the course during the semester.