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# Surveys and Experiments

### Available in 2012

Callaghan Campus Semester 1

### Previously offered in 2013, 2011, 2010, 2009, 2008, 2007, 2005, 2004

Using data to support decision making is essential in many disciplines, but how do we collect appropriate data? This course covers the design and analysis of surveys and experiments. Development of data collection instruments, methods for drawing a sample and estimation procedures appropriate to each design are described. The course aims to foster a sound understanding of the basic concepts and application of sampling and the principles of experimental design. Assignments and exercises are based on real problems.

This course is open to students in the BMath program (including double degree programs) or to students in other programs who have received explicit permission from the Head of Discipline of Statistics.

This course is shared by the Universities of Newcastle, Western Sydney and Wollongong as part of the Applied Statistics Education and Research Collaboration (ASEARC). In some years, the course will be beamed live from one of the other institutional partners using the Access Grid Room rather than being taught face-to-face at Newcastle.

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

1. gain familiarisation with the concepts and application of sampling and experimental design, and their use in modelling.
2. obtain practice with recognising and using key statistical skills.
3. develop skills in using the mathematical tools required to solve sampling and design problems.
4. develop skills and understanding of the collection and management of data.
5. develop skills and familiarity in identifying the statistical tools required to solve practical problems.
6. understand the principles of sampling, estimation and experimental design.
7. design and analyse surveys.
8. design and analyse experiments.
##### Content
Topics covered include:
. Design of surveys
. Design and estimation for a simple random sample
. Design and estimation for a stratified sample
. Design and estimation for a cluster sample
. Design and analysis of experiments including completely randomised designs, randomised block designs, incomplete block designs and factorial designs
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##### Assumed Knowledge
Introductory statistics
Introductory calculus and algebra
Statistics package such as SAS, SPSS, Stata, Minitab
External Mode
Internal Mode
##### Teaching Methods
Lecture
Integrated Learning
Computer Lab
##### Assessment Items
 Essays / Written Assignments Examination: Formal
##### Contact Hours
Computer Lab: for 1 hour(s) per Week for Full Term
Lecture: for 2 hour(s) per Week for Full Term