|Delivery Type||Delivery length / details|
|Practical||11 x 2 Hour Practicals|
|Lecture||33 x 1 Hour Lectures|
|Assessment Type||Assessment length / details||Proportion|
|Semester Assessment||Course work||30%|
|Semester Exam||2 Hours (written examination)||70%|
|Supplementary Exam||2 Hours (written examination)||100%|
On completion of this module, a student should be able to:
1. explain the rationale behind, and the underlying theory of, the analysis of variance;
2. explain the issues that arise in extending regression from one predictor variable to two;
3. carry out appropriate analyses and draw conclusions.
This module covers the theory of some of the most commonly used statistical techniques - regression and the analysis of variance. It also includes practical application of these important techniques.
This module will provide a thorough grounding in the basic theory associated with some important statistical models.
2. One way classification: the one way ANOVA model. Decomposition of the sum of squares. The ANOVA table and expected mean squares. Distribution of mean squares. The F-test. The treatment effects model. Random effects model. Unbalance design. The idea of blocking. Contrasts.
3. Higher order classification: The two way (balanced) model with replication. Decomposition. Interaction. Further contrasts and multiple comparisons. Expansion to higher order models.
This module is at CQFW Level 6