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Description
This module aims to provide an introduction to the statistical aspects relating to the design of experimental and observational studies, and to introduce associated methods of statistical analysis. It is intended for students registered on the Masters degree programmes offered by the Department of Statistical Science (including the CSML, DSML and MASS programmes).听For these students, the academic prerequisites for this module are met either through earlier compulsory study within (UG) or successful admission to (PGT) their current programme.
Intended Learning Outcomes
- have an understanding of the basic ideas of experimental design and observational studies;
- be able to analyse data from a variety of experimental designs by the analysis of variance;
- be able to assess the appropriateness of various sampling schemes and perform appropriate analyses.
Applications - this module addresses the issues of what data are needed to answer a particular substantive question, and conversely what questions can reasonably be answered using data that may be available. These issues are fundamental to quantitative analyses in all application areas.
Indicative Content - Principles of experimental design: planning of experiments, comparative experiments, common designs (completely randomised, randomised blocks, Latin square, factorial experiments, nested, fixed and random effects), associated analyses of variance in the R software. Observational studies versus experiments: problems of bias, confounding, difficulty of causal interpretation. Observational studies: planning, matching, adjusting for confounding variables, cohort studies, case-control studies, data analysis. Sampling: target and sampled populations, finite populations, simple random sampling, stratification and cluster sampling, ratio and regression estimators.
Key Texts - Available from .
Module deliveries for 2024/25 academic year
Last updated
This module description was last updated on 8th April 2024.
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