Statistical Design & Analysis

 IER specializes in finding solutions to applied resource problems using cutting-edge statistical and analysis tools.

  • Biological hypothesis driven mark-recapture and survival analysis to test hypothesis regarding factors affecting population size, trend, and demography using information theoretic model selection  methods. 
  • Habitat selection and occupancy models to determine resources most selected by wildlife species and assess trends in occupancy of habitats.
  • Analyses of covariance that allow testing of research or management hypotheses while controlling for other extraneous factors.
  • Data-driven population viability analysis to evaluate conservation and research strategies for bird and mammal species.
  • Design and analysis of water & sediment quality monitoring projects.
  • Comparisons of macroinvertebrate communities to regional reference conditions using the Canadian Biomonitoring Network Tools (CABIN)
  • Before-After Control-Impact (BACI) Studies
  • Multivariate statistical techniques, such as principal component analysis, canonical correspondence, step-wise regressions, and other approaches.

Statistical analysis techniques

IER uses general and advanced statistical methods ranging from concise graphical displays to complex analytical models.    IER provides expertise in:

  • Descriptive & general analyses
  • Linear & non-linear models
  • Mixed models and generalized linear models
  • Multivariate analyses
  • Survival analyses
  • Randomization methods
  • Mark-recapture methods
  • Occupancy models
  • Distance sampling
  • Resource selection functions
  • Telemetry & home range estimation