An R Introduction to Statistics

coda

Hierarchical Linear Model

  Linear regression probably is the most familiar technique in data analysis, but its application is often hamstrung by model assumptions. For instance, if the data has a hierarchical structure, quite often the assumptions of linear regression are feasible only at local levels. We will investigate an extension of the linear model to bi-level hierarchies.

Bayesian Inference Using OpenBUGS

  In our previous statistics tutorials, we have treated population parameters as fixed values, and provided point estimates and confidence intervals for them. An alternative approach is the Bayesian statistics. It treats population parameters as random variables. Probability becomes a measure of our belief in possible outcomes. With new tools like OpenBUGS, tackling new problems requires building new models, instead of creating yet another R command.