Experimental Design & Analysis

Unit Outline (Higher Education)

Level of Unit in Course

AQF Level(s) of Course

Level of Unit in Course

Introductory

Intermediate

Effective Term:

2024/20

Institute / School :

Institute of Innovation, Science & Sustainability

Unit Title:

Experimental Design & Analysis

Unit ID:

STATS2100

Credit Points:

15.00

Prerequisite(s):

(MS501 or STATS1000)

Co-requisite(s):

Nil

Exclusion(s):

(MS601)

ASCED:

010103

Other Change:

Brief description of the Unit

This unit introduces the key concepts underlying the design and analysis of statistical experiments. A range of experimental designs is considered. Data from various disciplinary contexts is utilised, and there is a strong emphasis on computing skills, interpretation of computer output and communication of statistical results and conclusions.

Grade Scheme:

Graded (HD, D, C, P, MF, F, XF)

Work Experience Indicator:

Placement Component: No

Supplementary Assessment:

Where supplementary assessment is available a student must have failed overall in the Unit but gained a final mark of 45 per cent or above, has completed all major assessment tasks (including all sub-components where a task has multiple parts) as specified in the Unit Description and is not eligible for any other form of supplementary assessment

Course Level:

Learning Outcomes:

Knowledge:

K1.	describe the concepts of experimental design, determine the design used in a particular practical situation, and identify the factors relevant to the situation;

K2.	choose appropriate experimental design techniques in context of the problem;

K3.	identify, analyse and report on a selection of advanced experimental designs;

K4.	describe the concept of power in relation to experimental design, and perform power calculations for simple designs;

K5.	interpret the results and computer output from all of the above designs and present clear, orderly and informative statistical summaries and technical reports.

Skills:

S1.	use technology to perform analysis of variance, including estimation of contrasts, planned and post hoc comparisons;

S2.	perform formal statistical analysis of data from a variety of disciplines;

S3.	use technology to generate and then interpret computer output and communicate statistical results and conclusions.

Application of knowledge and skills:

A1.	build and apply experimental designs for the real-world problems.

Unit Content:

Topics may include:
1. one-way ANOVA with multiple comparisons and planned and post hoc comparisons;
2. factorial designs and interactions;
3. power analysis;
4. fixed and random effects models;
5. balanced incomplete block designs;
6. latin squares and split plot designs;
7. hierarchical (nested) designs;
8. repeated measures designs.

Graduate Attributes:

	Learning Outcomes Assessed	Assessment Tasks	Assessment Type	Weighting
1.	K1-K5; S1-S3; A1	Practical use of appropriate statistical packages, and interpretation of output.	Weekly laboratory exercises	0 - 10%
2.	K1-K5; S1-S3; A1	Read, research and apply various aspects of experimental designs.	Assignments	40 - 50%
3.	K1-K5; S1-S3; A1	Attend lectures, read and summarise theoretical aspects of the unit	Examination(s)	50 - 60%

Adopted Reference Style:

APA

Professional Standards / Competencies:

Standard / Competency

Threshold Learning Outcomes - Mathematics: Initial

Attribute			Assessed	Level
1 Understanding
	1.1 Demonstrate a coherent understanding of the mathematical sciences.
		1.1.1 Ability to construct logical, clearly presented and justified arguments incorporating deductive reasoning.	Yes	Intermediate
		1.1.2 Understanding of the breadth of the discipline, its role in other fields, and the way other fields contribute to development of the mathematical sciences.	Yes	Intermediate
2 Knowledge
	2.1 Exhibit depth and breadth of knowledge in the mathematical sciences.
		2.1.1 Knowledge of the principles and concepts of a broad range of fundamental areas in the mathematical sciences.	Yes	Intermediate
		2.1.2 Well-developed knowledge in at least one sub-discipline of the mathematical sciences.	Yes	Intermediate
3 Inquiry and Problem Solving
	3.1 Investigating and solving problems using mathematical and statistical methods.
		3.1.1 Ability to formulate and model practical and abstract problems in mathematical and / or statistical terms using a variety of methods.	Yes	Intermediate
		3.1.2 Ability to apply mathematical and / or statistical principles, concepts, techniques and technology to solve practical and abstract problems and interpret results critically.	Yes	Intermediate
4 Communication
	4.1 Communicate mathematical and statistical information, arguments, or results for a range of purposes using a variety of means.
		4.1.1 Appropriate interpretation of information communicated in mathematical and statistical form.	Yes	Intermediate
		4.1.2 Appropriate presentation of information, reasoning and conclusions in a variety of modes, to diverse audiences (expert and non-expert).	Yes	Intermediate
5 Responsibility
	5.1 Demonstrate personal, professional and social responsibility.
		5.1.1 Ability to self direct learning to extend their existing knowledge and that of others.	No	Intermediate
		5.1.2 Ability to work effectively and responsibly in an individual or team context.	Yes	Intermediate
		5.1.3 Ethical application of mathematical and statistical approaches to solving problems.	Yes	Intermediate