STA508 Experimental Design and Analysis (PG) (8)

Proper experimental design and sampling is a prerequisite to the efficient and cost effective resolution of comparative quantitative research questions. This subject introduces experimental design based analysis and sampling techniques through the use of examples from research and professional settings. It also extends the basic methodology with applications. Students will gain experience in using software packages, and in evaluating and presenting results in the form of a standard statistical report as used in professional practice.

Availability

Session 1 (30)
Online
Wagga Wagga Campus

Continuing students should consult the SAL for current offering details: STA508. Where differences exist between the Handbook and the SAL, the SAL should be taken as containing the correct subject offering details.

Subject Information

Grading System

HD/FL

Duration

One session

School

School of Computing and Mathematics

Enrolment Restrictions

Not available to students who have completed STA308.

Available to postgraduate students only.

Assumed Knowledge

STA201 or  STA401 or STA501

Incompatible Subjects

STA308

Learning Outcomes

Upon successful completion of this subject, students should:
  • be able to design, and check the design of, standard experiments reflective of professional practice;
  • be able to perform the analysis of such experiments using appropriate statistical protocols;
  • be able to communicate results and justify interpretations in terms of the original problem with logic and precision;
  • be able to evaluate and present results, with an integrated understanding of the underlying theory, in the form of a standard statistical report;
  • be able to critically test any assumptions underpinning the use of the linear model;
  • be able to demonstrate basic knowledge of survey methods and its application to a wide range of problems; and
  • be able to perform design and analysis tasks on recognised software platforms.

Syllabus

This subject will cover the following topics:
  • Principles of experimental design.
  • Simple linear regression: review and extension.
  • Polynomial and multiple linear regression.
  • Principles of experimental design; including completely randomised designs, randomised block designs and Latin square designs.
  • Multiple comparison methods.
  • Diagnostic checking of the basic model.
  • The analysis of experiments with factorial treatment structures.
  • Analysis of variance.
  • Analysis of covariance.
  • Introduction to survey methods.
  • Statistical software.

The information contained in the CSU Handbook was accurate at the date of publication: January 2020. The University reserves the right to vary the information at any time without notice.

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