S-022: Statistical Computing and Simulation Inference

Semester:

Spring

Offered:

2016

This course teaches a synergetic blend of statistical computing and re-sampling (permutation and bootstrap) methods. Statistical computing allows more flexible investigation of data, such as generating customized visualizations and summarizations or custom-tailoring an analysis. Re-sampling methods can often allow for principled data analysis in circumstances where, for example, the parametric assumptions behind more traditional analyses such as linear regression are held in doubt or the sample sizes are too small for asymptotics to hold. They can also be used when ones estimands and...

S-043/Stat-151: Multilevel and Longitudinal Models

Semester:

Fall

Offered:

2015

Data often have structure that needs to be modeled explicitly. For example, when investigating students' outcomes we need to account for the fact that students are nested inside classes that are in turn nested inside schools. If we are watching students develop over time, we need to account for the dependence of measurements across time. If we do not, our inferences will tend to be overly optimistic and wrong. The course provides an overall framework, the multilevel and generalized multilevel (hierarchical) model, for thinking about and analyzing these forms of data. We will focus on...