Statistics prof helps students avoid wrong conclusions, fallible inferences
By Craig Brandhorst, firstname.lastname@example.org, 803-777-3681
If you think you hate statistics or they make you nervous, you might just be the perfect student for Amanda Fairchild.
The associate professor of psychology is out to demystify statistics for University of South Carolina master’s and Ph.D. candidates, who need Fairchild’s courses to complete their degrees but do not always see themselves as numbers people.
“When you’re dealing with a subject like statistics, you inevitably get people coming in with anxiety from the outset saying things like, ‘I’m not good at math,’” Fairchild says. “Over the years though, I’ve come to understand that what’s more often true is that students simply lack confidence in statistics due to ineffective teaching in their past.”
Fairchild’s personal experience with anxiety has enhanced her ability to empathize with student fears. She believes that a patient and compassionate approach in the classroom helps to allay student student fears and to incite new curiosity for statistical methods, but her success as a teacher hinges more on the unique perspective that she brings to her subject.
“My approach, really, is to teach statistics as a language, with an emphasis on the art of speaking that language well in order to do science well,” she says. “Much as there’s an art to communicating with language, there’s an art to communicating with statistics.”
Originally, Fairchild set off to do graduate work in social psychology at James Madison University — “I didn’t dream of becoming a methodologist as a young girl,” she says — but a special professor sparked her enthusiasm for quantitative methods.
When she encountered published research that didn’t reflect what she was learning in class, she approached her professor and expressed that the researchers seemed to be making fundamental mistakes, conducting studies in a manner that could lead to bias, inaccurate conclusions, and fallible inferences. She wondered, “How could the research be scientifically valid if not grounded in proper techniques?”
Fairchild’s professor told her that many people don’t see statistics as a necessary prerequisite of good science. “That really struck me and caused me to change direction in grad school.”
Instead of working toward a master’s in social psychology, as planned, Fairchild pursued a master’s in assessment, measurement and statistics, going on to complete a Ph.D. in quantitative psychology. She studied under a mentor who underscored the importance of conducting quantitative work that was accessible to applied scientists. Now her mission is to convey the crucial role of statistics in conducting applied research to her own students.
“I have developed a little band of methods warriors,” she says. “I get my students to ask, ‘Wait, if I don’t have good measurement or a good research design or a good statistical model, how can I have a good substantive study?’
“Even if they don’t love the subject as I do, I know that I am sending them out with a strong statistical foundation that will allow all of us to be proud of the training that they received in our program.”
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