This blog series is devoted to the question of how statistics and errors in the geospatial sciences are connected, applied, worked with, and generally how you get along with and live with errors.
Starting from first principles, and first causes, we will attempt to build a picture of statistics and errors that may make a bit more sense than more theory-based discussions. Ultimately, the purpose is to provide the reader with a deep understanding of the nature of errors and their impact on everything that happens with spatial, data, information, knowledge, processing, and what happens after that.
Understanding errors in geospatial endeavors, be they measurement, computation, analysis or representation, is a weak area in the wider geospatial sciences. This blog will attempt to fill in a few gaps in that understanding.