Structures in applied statistics (frequentistic approach)
Self assessment What should we repeat ?.pdf
Basics
   Causation and Causal Inference Lacking Control Increases Illusory Pattern Perception
   Confounding Confounding .pdf
Experiments, Observations, Natural experiments
   Sampling designs Sampling and Experimental Design  
   Flaws in experiments
   Observational surveys and studies Surveys and Studies
Modelling
   Ordinary: Linear, nonlinear, n-step modelling GLM Examples;  GLM and some other models;  
   Dynamical: Agent based modelling "Probability framework":
   Flaws: Model artifact
   Problems: Endogeneity and confounding
Measures
   Testing (p-value) and estimating (confidence interval)
   Power and Sample Size How to plan the sample size?
Multilevel modeling
   Clustered Regression
   Hierarchical nested Models
   Longitudinal Models
Resampling  
   Permutation; Cross-Validation; Jackknife; Bootstrap Exact tests and confidence intervals; model checking
Miscellaneous
   ROC (Receiver Operating Characteristic)
   Factor analysis
   Cluster analysis
New within last 6 months: In discussion or use, will be improved  Final version