Course Title: Design and Analysis of Experiments

Part A: Course Overview

Course Title: Design and Analysis of Experiments

Credit Points: 12.00

Terms

Course Code

Campus

Career

School

Learning Mode

Teaching Period(s)

MATH1302

City Campus

Postgraduate

145H Mathematical & Geospatial Sciences

Face-to-Face

 Sem 1 2006,
Sem 2 2014,
Summer2016

MATH1302

City Campus

Postgraduate

171H School of Science

Face-to-Face

 Sem 1 2018,
Sem 1 2020,
Sem 1 2022

Course Coordinator: Dr. Stelios Georgiou

Course Coordinator Phone: +61 3 9925 3158

Course Coordinator Email: stelios.georgiou@rmit.edu.au


Pre-requisite Courses and Assumed Knowledge and Capabilities

 

Assumed Knowledge

Basic knowledge of statistics. Some knowledge of statistical packages such as MINITAB and SAS would be beneficial.


Course Description

This course deals with the concepts and techniques used in the design and analysis of experiments. The concepts and different models of an experimental design will be studied, leading to their statistical analysis based on linear models and appropriate graphical methods.


Objectives/Learning Outcomes/Capability Development

This course contributes to the following Program Learning Outcomes for MC004 Master of Statistics and Operations Research and MC242 Master of Analytics:

Personal and professional awareness

  • the ability to contextualise outputs where data are drawn from diverse and evolving social, political and cultural dimensions
  • the ability to reflect on experience and improve your own future practice
  • the ability to apply the principles of lifelong learning to any new challenge.

Knowledge and technical competence

  • an understanding of appropriate and relevant, fundamental and applied mathematical 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 relationship between the purpose of a model and the appropriate level of complexity and accuracy.

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.

Information literacy

  • the ability to locate and use data and information and evaluate its quality with respect to its authority and relevance.

 


 On completion of this course you should be able to:

  1. Critically review basic concepts and models of experimental design.
  2. Analyse the results of a designed experiment in order to conduct the appropriate statistical analysis of the data
  3. Interpret statistical results from an experiment and report them in non-technical language.


Overview of Learning Activities

 

You will be actively engaged in a range of learning activities such as lectorials, tutorials, practicals, laboratories, seminars, project work, class discussion, individual and group activities. Delivery may be face to face, online or a mix of both. 

You are encouraged to be proactive and self-directed in your learning, asking questions of your lecturer and/or peers and seeking out information as required, especially from the numerous sources available through the RMIT library, and through links and material specific to this course that is available through myRMIT Studies Course


Overview of Learning Resources

 

RMIT will provide you with resources and tools for learning in this course through myRMIT Studies Course. 

There are services available to support your learning through the University Library. The Library provides guides on academic referencing and subject specialist help as well as a range of study support services. For further information, please visit the Library page on the RMIT University website and the myRMIT student portal.


Overview of Assessment

Assessment Tasks:

Assessment Task 1: Take home Assignments
Weighting 50%
This assessment task supports CLOs 1, 2 & 3

Assessment Task 2: Online summative tests
Weighting 50% 
This assessment supports CLOs 1, 2 & 3

If you have a long-term medical condition and/or disability it may be possible to negotiate to vary aspects of the learning or assessment methods. You can contact the program coordinator or Equitable Learning Services if you would like to find out more.