Correlated data arise in many situations, particularly when observations are made over time and space or on individuals who share certain underlying characteristics. This course covers techniques for exploring and describing correlated data, along with statistical methods for estimating population parameters (mostly means) from these data. The focus will be primarily on generalized linear models (both with and without random effects) for normally and non-normally distributed data. Wherever possible, techniques will be illustrated using real-world examples. Computing will be done using R and SAS.prereq: Regression at the level of PubH 6451 or PubH 7405 or Stat 5302. Familiarity with basic matrix notation and operations (multiplication, inverse, transpose). Working knowledge of SAS or R (PubH 6420).
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