When used inappropriately, statistical models may give rise to misleading conclusions. Checking that a given model is an appropriate representation of the data is therefore an important step.

Kevin Burke, M. C. Jones, Angela Noufaily, A flexible parametric modelling framework for survival analysis, Journal of the Royal Statistical Society. Series C (Applied Statistics), Vol. 69, No. 2 ...

A second course in statistics with an emphasis on data analysis with applications in the social sciences. Students will gain hands on experience using R-- a programming language and software ...

Scandinavian Journal of Statistics, Vol. 32, No. 2 (Jun., 2005), pp. 223-240 (18 pages) We review and extend some statistical tools that have proved useful for analysing functional data. Functional ...

Abstract: Assumptions play a pivotal role in the selection and efficacy of statistical models, as unmet assumptions can lead to flawed conclusions and impact decision-making. In both traditional ...

For each indicator, the latest figure and its one-year, five-year, and 10-year changes are easy to understand in terms of raw data, but we need supplementary statistical analysis to determine ...

Numerical models and satellite observation are fundamental to understanding environmental systems and change. The MSc in Environmental Modelling and Data Analysis will provide you with the skills to ...

Learning how to perform statistical data analysis in Microsoft Excel can help you improve your analytics and reporting. This guide takes you ...