This module looks at the common statistical tools applied in the management of healthcare environments.
Experimental Design and Analysis of variance:
Principles of experimental design: Replication, randomisation, blocking. Fully randomised designs, randomised block designs; Advantages of cross-classification of factors to traditional one-at-a-time experiments. Analysis of Variance:The variance ratio test. One-way analysis of variance. Two-way analysis of variance without interaction.Two-way analysis of variance with interaction.
Regression Analysis:
Linear, curvilinear and multiple regression. Choice of model: transformations. Validity of model: analysis of residuals. Predictions: interpolation and extrapolation.
Applied Statistics:
Significance: Statistical knowledge and domain knowledge, statistical significance and practical significance, robustness of statistical methods to departures from assumptions. Atmospheric dispersion modelling: the Gaussian model, types of computer models, analysis of output. Calibration curves: absorbance and concentration, the method of standard additions. Bioassays: potency estimation.
Module Content & Assessment | |
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Assessment Breakdown | % |
Other Assessment(s) | 100 |