STA308 Experimental Design and Analysis (8)

Proper experimental design is a prerequisite to the efficient and cost effective resolution of comparative quantitative research questions. This subject introduces experimental design and analysis by examples and by the study of the underlying linear model. Use of appropriate computer packages allows testing of assumptions and investigation of advanced topics. Extensions of the basic methodology are explored.

Subject Outlines
Current CSU students can view Subject Outlines for recent sessions. Please note that Subject Outlines and assessment tasks are updated each session.

Availability

Session 1 (30)
On Campus
Wagga Wagga Campus
Online
Wagga Wagga Campus

Continuing students should consult the SAL for current offering details: STA308. 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 STA508.

Prerequisites

STA201 or STA401 or QBM217

Subject Relationships

STA508 Similar content

Incompatible Subjects

STA508

Learning Outcomes

Upon successful completion of this subject, students should:
  • be able to identify situations for which a linear model is appropriate;
  • be able to design, and check the design of, basic experiments;
  • 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;
  • be able to critically test any assumptions underpinning the use of the linear model;
  • 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.
  • Statistical software.

Contact

Current Students

For any enquiries about subject selection or course structure please contact Student Central or ask@csu.edu.au or phone on 1800 275 278.

Prospective Students

For further information about Charles Sturt University, or this course offering, please contact info.csu on 1800 275 278 (free call within Australia) or enquire online.

The information contained in the 2018 CSU Handbook was accurate at the date of publication: August 2018. The University reserves the right to vary the information at any time without notice.

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