UT scientist uses algal bloom toxin-measuring research in new statistics textbook

October 6, 2016 | News, Research, UToday, Natural Sciences and Mathematics
By Christine Billau

Two years after the Toledo water crisis left half a million residents without safe tap water for three days, a University of Toledo faculty researcher published a new statistics textbook for scientists with Lake Erie algal bloom toxins as featured examples.

Dr. Song Qian, associate professor in the Department of Environmental Sciences, included his latest research related to the methods of measuring and reporting microcystin in the second edition of Environmental and Ecological Statistics With R.



“The increasing severity of algal blooms makes the book especially relevant,” Qian said. “We use many of the same methods for a very large-scale analysis of all the Great Lakes, as well as a very small-scale data analysis in the lab.”

Qian concentrated on making data analysis and statistical modeling accessible and understandable by applying it to real-world examples in environmental and ecological literature.

“When you package the data together with a complicated problem, such as the algal blooms here, it makes relating to the audience much easier,” Qian said. “I believe that studying statistics is not the same as learning mathematics. Statistics requires subject matter knowledge. Without knowing the nature of the data in a particular field and how the data were collected, we can rarely apply statistics well. Statistics is often the most challenging course for environmental graduate students. I hope that examples such as measuring Lake Erie harmful algal bloom toxins would make the learning process easier, especially in making connections to their individual research subjects.”

The book has received reviews on Amazon.com from environmental statistics scholars worldwide.

“The R code included in the book outlines key computational procedures and provides a workable foundation upon which researchers can conduct scientific inference and statistical analysis with their own data,” Dr. Kenneth H. Reckhow, professor emeritus at Duke University, wrote.

“This book gives us a new way to teach statistics to biological and ecological students at research level,” Dr. Bo-Ping Han, professor in the Department of Ecology at Jinan University in China, wrote.

“I particularly enjoyed the third section of the book covering interesting areas of advanced statistical modeling, where the reader can find many didactical examples that are highly relevant to environmental management such as the problem of Cryptosporidium in drinking water, the uncertainty in water quality measurements using the ELISA method as an example, or the threshold indicator taxa analysis,” wrote Dr. George Arhonditsis, professor and chair of the Department of Physical and Environmental Sciences at the University of Toronto.

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