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 ...

Data analysis and graphics using R: an example-based approach. Cambridge University Press Gelman, A., & Hill, J. (2006). Data analysis using regression and multilevel/hierarchical models. Cambridge ...

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.

Data modeling is the framework that lets data analysis use data for decision-making. A combined approach is needed to maximize data insights.

Multiple-bias models provide alternatives that allow one systematically to integrate major sources of uncertainty, and thus to provide better input to research planning and policy analysis. Typically, ...

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

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 ...

It will cover an introduction to quantitative research design and causal inference, exploratory data analysis and data visualisation, generalised linear models, and generalised latent variable models ...