The Statistical Laboratory, originally established in 1977 to provide
statistical consulting services for the faculty and students of the
University, has expanded its mission to include contract consulting with
industrial, university, government and other private clients.
Through its ties with a research statistics department, a university
statistical laboratory may be primarily associated with modern,
sophisticated data analysis. However, the Stat Lab at USC has experience
in all phases of a research project including:
- experimental design
- data collection
- data entry and management
- data description and presentation
- data analysis
- reports and presentations
We have also accumulated extensive experience with survey projects and
can provide help in designing survey instruments, developing survey
sampling plans and conducting surveys.
Recent Stat Lab projects have included the following clients:
Turner Environmental Services. The Stat Lab developed statistical
methods to aid in the spatial and temporal modeling of several analytes
in a variety of environmental conditions. We developed spatiotemporal
models for analytes in monitoring wells at waste storage and landfill
sites and developed tests for trends over time.
South Carolina Department of Natural Resources. The Stat Lab has been
retained to provide consulting on miscellaneous freshwater fisheries
projects, including growth curve modeling of largemouth bass in SCís
reservoirs, population estimation of anadromous species in the
Santee-Cooper lakes, and sample size recommendations for surveys of
SC Department of Public Safety. The Stat Lab has designed and analyzed
the annual survey of statewide seat-belt compliance for over ten years.
Field surveys in 16 counties are organized and drivers and front-seat
passengers are monitored for compliance. The Stat Lab uses stratified
multistage sampling and computes Horvitz-Thompson-type estimators and
standard errors of compliance rates.
Jones Ecological Research Center. The Stat Lab has worked with the Jones
Ecological Research Center in Ichauway, GA to analyze fire behavior in
longleaf pine savannas. Analysis has included standard spatial methods
to characterize fuel "cells" and Bayesian spatiotemporal modelling to
analyze fire temperature as a function of fuel characteristics and
SC DOE. The Stat Lab has analyzed PACT (Palmetto Achievement Challenge
Tests) data for SC students to identify test items that distinguish
between students with disabilities and the general student population.
The DIF (Differential Item Functioning) analyses we conducted will be
used to modify individual learning plans for students with disabilities.