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Courses

Course material for USC PM522b Statistical Inference, USC PM569 Spatial Statistics and USC PM566 Introduction to Health Data Science.

Statistical Inference:

Course text Casella and Berger Statistical Inference, 2nd ed. 2002
  • Slides 1: Random sampling, sampling distributions, order statistics.
  • Slides 2: Sufficiency principle (sufficient, minimal sufficient, complete sufficient statistics), ancillary statistics, Basu's Theorem, Likelihood principle.
  • Slides 3: Methods for finding point estimators including maximum likelihood, numerical methods for maximum likelihood, moment generating functions, method of moments.
  • Slides 4: Evaluating estimators -- bias, MSE, MVUE
  • Slides 5: Hypothesis testing and interval estimation
  • Slides 6: Asymptotic evaluations -- consistency, effeciency, robustness, asymptotic LRT, asymptotic interval estimates, bootstrap.
  • Slides 7: ANOVA and linear regression

Spatial Statistics:

  • Introduction: spatial data and spatial data types
  • Geostatistics 1: spatial semivariance and covariance
  • Geostatistics 2: fitting semivariogram and covariance functions
  • Geostatistics 3: kriging and spatial interpolation
  • Areal 1: neighbourhoods and adjacency
  • Areal 2: global and local measures of association
  • Areal 3: spatial autoregressive models
  • Point pattern 1: Poisson processes and complete spatial randomness
  • Point pattern 2: Point process modeling and cluster detection
  • Point pattern 3: Markov modeling and inhibition processes

Data Science:

  • Check out the course here

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