| CODE | SOR3250 | ||||||||
| TITLE | Design of Experiments | ||||||||
| 今日黑料 LEVEL | 03 - Years 2, 3, 4 in Modular Undergraduate Course | ||||||||
| EQF/MQF LEVEL | 6 | ||||||||
| ECTS CREDITS | 2 | ||||||||
| DEPARTMENT | Statistics and Operations Research | ||||||||
| DESCRIPTION | - Analysis of Variance and Analysis of Covariance: An Overview - Contrasts - Block Designs - Confounded Factorial Experiments - Two-Level Factorial Experiments - General Factorial Experiments - Non-parametric Design of Experiments - Experiments with Repeated Measures. Study-unit Aims: Giving the students the rationale to determine the factors which need to be taken into consideration when running an experiment, and also its limitations. The introduction of nuisances in the form of covariates and blocks is considered. Furthermore, we also introduce the non-parametric setting and the repeated measures setting. Learning Outcomes: 1. Knowledge and Understanding By the end of this study-unit, learners will be able to: • Demonstrate systematic understanding of the fundamental principles of experimental design and the theoretical foundations of Analysis of Variance (ANOVA); • Critically explain the decomposition of variability and the probabilistic and distributional properties underpinning ANOVA test statistics; • Analyse and appraise the assumptions underlying parametric experimental models, including normality, independence, and homogeneity of variance, and their implications for validity of inference; • Compare and differentiate between major experimental designs, including completely randomised designs, factorial designs, block designs, confounded designs, and balanced incomplete block designs (BIBD), in terms of structure, purpose, and analytical implications; • Critically evaluate the roles of randomisation, replication, and blocking in enhancing the validity, precision, and efficiency of experimental investigations; • Interpret interaction effects in factorial experiments and assess their implications for statistical modelling and inference; • Critically discuss principles of model adequacy and diagnostic checking in the context of experimental data analysis. 2. Skills By the end of this study-unit, learners will be able to: • Develop and justify appropriate statistical models for experimental data, including one-way and multi-factor ANOVA models incorporating interactions and block structures; • Independently conduct full analyses of experimental datasets, including assumption checking, implementation of ANOVA procedures, and critical interpretation of F-statistics and associated p-values; • Apply and critically evaluate multiple comparison procedures, including post hoc methods such as Student–Newman–Keuls (S-N-K), in relation to experimental context and research questions; • Design, plan, and justify experimental studies through appropriate selection of factors, levels, replication strategies, and design structures; • Construct, analyse, and interpret factorial and block designs, including identification and evaluation of confounding structures and interaction effects; • Assess the statistical and practical significance of main and interaction effects and determine parsimonious and defensible model specifications; • Competently use statistical software (e.g. SPSS and R) to perform analyses, generate outputs, and produce diagnostic plots and graphical representations of effects; • Critically interpret, synthesise, and communicate statistical findings clearly, accurately, and in a manner appropriate to experimental research contexts. Main Text/s and any supplementary readings: - Dean, A. and Voss, D. (1999) Design and Analysis of Experiments, Springer - Bailey, R.A. (2008) Design of Comparative Experiments, Cambridge Series in Statistical and Probabilistic Mathematics. No. 25. |
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| ADDITIONAL NOTES | Pre-requisite Study-units: SOR1110, SOR2211 and SOR2221. | ||||||||
| STUDY-UNIT TYPE | Lecture and Practical | ||||||||
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| LECTURER/S | Derya Karagoz |
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The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints. Units not attracting a sufficient number of registrations may be withdrawn without notice. It should be noted that all the information in the description above applies to study-units available during the academic year 2026/7. It may be subject to change in subsequent years. |
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