Submitted by ghazishukur on August 21, 2012 - 15:05
This course will be run during week 39, 24 september - monday, 28 september 2012 at 10:00 to frieday 28 September 12:00 (full-time course) at the School of <?xml:namespace prefix = st1 ns = "urn:schemas-microsoft-com:office:smarttags" />Business and Economics, Linnaeu University, Växjö.
Introduction to spatial data analysis, representing space, interfacing geographical information systems, space-time data, spatial statistics overview (point patterns, geostatistics, areal data). Use of GIS and spatial statistics for radioecological modeling and mapping using Chernobyl- and Fukushima-related data, focusing on public health protection.
Mathematical background (limits, series, order relations and rates of convergence, continuity, sets)
Measure theoretic foundations of probability (probability triplets, random variables, independence, expected values, change of variable)
Stochastic convergence (almost sure convergence, convergence in probability, convergence in distribution, laws of large numbers, central limit theorems, non-iid stochastic variables)
Conditional probability and expectation
Statistical tests (size and critical values, power, efficiency, asymptoti
Incomplete data is a common phenomenon in longitudinal studies based on surveys and/or population registers. In such studies individuals are followed through time and data may be incomplete due, e.g., to drop out/attrition (individuals intentionally leave the study, individuals leave the study because they move or die, etc.) and censoring (due to end of study, death, etc). Incomplete data may also arise due to selection mechanisms, for instance, in meta-analyses (publication bias) and causal inference in observational studies.
Mathematical background (limits, series, order relations and rates of convergence, continuity, sets)
Measure theoretic foundations of probability (probability triplets, random variables, independence, expected values, change of variable)
Stochastic convergence (almost sure convergence, convergence in probability, convergence in distribution, laws of large numbers, central limit theorems, non-iid stochastic variables)
