Data analysis and modelling


What to recognize and which inductions?


Data are analyzed to support decision processes. The more precise the problems are formulated, the better a quantitative result be used, e.g., with:


  • Visualization of data
  • Regression (generalized linear models)
  • Analysis of variance and covariance (ANOVA, ANCOVA)
  • Reliability, lifetime or Weibull analysis
  • Nonparametric methods
  • Monte-Carlo simulation, Bayesian and Bootstrap methods
  • Numerical and stochastic optimization