Louisiana State University Shreveport (LSUS) and BioMedware are pleased to announce a workshop providing FREE in-person training on BioMedware software for GIS data. The software is used for the visualization, analysis, modeling, and interactive exploration of spatiotemporal data and provides a variety of regression and spatial modeling tools.
The training workshop will take place on Thursday, June 15th and Friday, June 16th on the LSUS campus and will be taught by BioMedware’s Chief Scientist, Dr. Pierre Goovaerts. To succeed in this workshop, we recommend participants have basic experience with or knowledge of GIS. Limited spots are available and seats are filled on a first-come, first-serve basis, with priority given to LSUS students, faculty, and staff.
Please email Dr. Amy Erickson if you are interested and want to reserve a seat at amy.erickson@lsus.edu.
Future Workshops
BioMedware is planning future workshops at our offices in Ann Arbor, Michigan to provide training on BioMedware software. Example topics include:
- Loading the data. Bringing in GIS data from other platforms; Handling and time-stamping of space-time data; Missing data; data types and type casting; Vector data formats; Raster data formats; spatial and time-dynamic data.
- Data discovery and pattern recognition. Space-time pattern recognition and hypothesis generation using linked windows and statistical and cartographic brushing; time-animation.
- Statistical graphics. Time-enabled histograms, scatterplots, boxplots, heat maps, and other visualizations.
- Maps. Displaying your data; using map tiler; map animation; color schemes; point maps; choropleth maps; continuous maps; map categories.
- Correlation assessment: Approaches to revealing spatial, temporal and multivariate dependencies.
- Geostatistics. Kriging, co-kriging, space-time kriging, change of spatial support (downscaling, upscaling, side-scaling), noise-filtering, forecasts and predictions through space-time accounting for secondary information, stochastic simulation.
- Regression. Univariate; multivariate; linear; non-linear; joinpoint; spatial joinpoint, geographically-weighted regression.
- From data to hypothesis testing, modeling, and predictions. Putting it all together; assessing model fit; results comparison approaches.
- Focused topics include identifying space-time health disparities; exposure assessment and reconstruction; disease cluster analysis; uncertainty modeling, classification of service lines material, and many others.
Interested in attending? Please contact sales@biomedware.com expressing your interest in future training sessions and your contact information.