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A coordinated treatment of linear and generalized linear models and their application. Linear regression, analysis of variance and covariance, random effects, design and analysis of experiments, quality improvement, log-linear models for discrete multivariate data, model selection, robustness, graphical techniques, productive use of computers, in-depth case studies.

Details

  • Department: Statistics (STAT)
  • Units: 4
  • Prerequisites: STAT 102 or STAT 135, STAT 133
  • Tools:
  • Cluster(s): Mathematics/Statistics
  • Tags: Applied