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Articles 1 - 2 of 2
Full-Text Articles in Biostatistics
A Biological Assessment Of Water Quality In El Placer, Ecuador: The Effect Of Agriculture On Stream Health And The Quality Of Historical Versus Current Drinking Water Sources, Danielle Kleinberg
A Biological Assessment Of Water Quality In El Placer, Ecuador: The Effect Of Agriculture On Stream Health And The Quality Of Historical Versus Current Drinking Water Sources, Danielle Kleinberg
Independent Study Project (ISP) Collection
Although fresh water is one of Ecuador’s most abundant resources, high quality drinking water for its inhabitants is scarce (Wingfield et al., 2021). The most prevalent sources of water pollution in Ecuador are domestic waste, silver and gold mining, oil production, and agricultural chemicals (Buckalew et al., 1997). El Placer, a village located in Tungurahua, Ecuador, is highly dependent on agriculture as a source of income. The first objective of this study was to determine the effect of agriculture on the El Placer’s Tía Anita Stream through comparing the water quality at three sites with varying agricultural influence. The second …
A Bayesian Hierarchical Mixture Model With Continuous-Time Markov Chains To Capture Bumblebee Foraging Behavior, Max Thrush Hukill
A Bayesian Hierarchical Mixture Model With Continuous-Time Markov Chains To Capture Bumblebee Foraging Behavior, Max Thrush Hukill
Honors Projects
The standard statistical methodology for analyzing complex case-control studies in ethology is often limited by approaches that force researchers to model distinct aspects of biological processes in a piecemeal, disjointed fashion. By developing a hierarchical Bayesian model, this work demonstrates that statistical inference in this context can be done using a single coherent framework. To do this, we construct a continuous-time Markov chain (CTMC) to model bumblebee foraging behavior. To connect the experimental design with the CTMC, we employ a mixture model controlled by a logistic regression on the two-factor design matrix. We then show how to infer these model …