Data Analysis

Dr. Goovaerts can capitalize on his engineering degree, his computational skills and training in (geo)statistics to provide technically-sound and practical solutions to most projects dealing with the analysis of multivariate data distributed across space and time (see portfolio). Recent projects include:

  1. mapping soil dioxin contamination around the Dow Chemical Incinerator in Midland (MI),
  2. estimating soil arsenic contamination caused by ASARCO smelter in Tacoma (WA),
  3. mapping the spatial distribution of 43 different soil pollutants (organic and inorganic) over the entire Walloon region in Belgium,
  4. modeling arsenic in private groundwater wells in 11 counties in southeastern Michigan and exploring its impact on the incidence of prostate and bladder cancer,
  5. estimating the spatial extent and degree of oiling along Louisiana shorelines resulting from the Deepwater Horizon oil spill,
  6. modeling the distribution of PCBs and heavy metals in sediments of multiple water bodies in the Great Lake region,
  7. analyzing the impact of air pollution on low birth weight and pre-term delivery in Detroit airshed,
  8. mapping the risk of late-stage diagnosis for prostate cancer over the entire State of Florida,
  9. modeling the spatial and temporal distribution of lead in drinking water and blood in Flint, MI.

Dr. Goovaerts’ areas of expertise cover (non-exhaustive list):

  1. Multivariate statistics (e.g. principal component analysis, discriminant analysis, canonical analysis, MANOVA, multi-dimensional scaling),
  2. Regression (linear, non-linear, Poisson, logistic, spatial, geographically-weighted),
  3. tests of hypothesis (t-test, ANOVA),
  4. Cluster detection (Moran’s I, SatSCan),
  5. Temporal Trend Modeling
  6. Geostatistics (variogram analysis, (Co)kriging, probability mapping, stochastic simulation, space-time interpolation)