Subject Description | Upon completion of the subject, students should be able to:
understand and apply the basic concepts of study design, such as observational studies versus designed experiments, replication, randomisation, blocking and confounding, and recognise the effect of the design concepts on the interpretation of results;
recognise and apply experimental designs such as completely randomised, randomised block and Latin square designs;
construct and interpret appropriate graphs and tables for displaying and summarising data;
understand the basic concepts of statistical models such as estimation, predicted values, residuals, parameters and the normal distribution;
formulate, fit and interpret models involving one or two explanatory variables, which may be categorical, numerical, or one of each;
state the assumptions of simple models and use the data and residuals to check these assumptions;
understand the purposes and limitations of statistical inference, and use the main tools of inference, including measures of precision, confidence intervals, P-values, hypothesis tests and significance; and
use the statistical package Minitab to explore and analyse data, and interpret the output in terms of the original context of the data.
Topics include:
types of variables; observational studies and designed experiments; replication, randomisation and blocking; displaying and summarising data;
statistical models - formulation, estimation, checking and inference; comparing and selecting models; analysis of variance; linear regression;
standard errors, confidence intervals and hypothesis tests; experimental designs - randomised blocks, Latin squares, incomplete blocks; ANOVA with two factors; interaction; and
residual plots; transformations; multiple regression; combining categorical and numerical explanatory variables; contingency tables.
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