By Julia Mericle
Staff Writer
Giles Bootheway, finance professor at St. Bonaventure University, recently won the Best Paper Award for his work titled “Persistent Misconceptions Concerning Null Hypothesis Significance Testing” at the annual American Society for Business and Behavioral Sciences Conference (ASBBS).
His colleagues, Darwin King and Carl Case, respectfully professors of accounting and business information systems, also received a best paper award for their work titled, “Organizations Competing In The Realm Of Social Networking: An Analysis Of AACSB Accredited Schools Of Business.”
The Null Hypothesis Significance Test has existed informally for hundreds of years. However, British statistician Ronald Fisher formalized the procedure during the early 20th century and statisticians Egon Pearson and Jerzy Neyman popularized a more expansive version of the test in the 1930s, according to Bootheway.
The Null Hypothesis Significance Test is when a researcher makes a claim about a population parameter, which is a property that the researcher seeks to know more about, but is either impossible or far too expensive to attain more information on Null Hypothesis.
“Significance Testing allows (the researcher) to test that claim by calculating a ‘test statistic’ from sample data and comparing it to ‘critical value(s)’ drawn from a population distribution,” Bootheway said.
Because of the test’s simplicity, it faces criticism, even from writers who conduct it. According to Bootheway, he dismissed such critics, saying they don’t understand the procedure.
“(It’s) sort of like how a bad workman blames his or her tools,” Bootheway said.
As a finance professor in the School of Business, Bootheway stays informed on current literature of the subject.
Bootheway said many professors do not necessarily get an idea and write a paper. Rather, while staying in touch with advancements in their subject area, they are made aware of current themes they may or may not agree with.
Through his research, Bootheway noticed that he disagreed with certain strands of the literature regarding Hypothesis Significance Testing.
“I’ve seen quite a few papers criticizing hypothesis testing. I read those papers, and I said, ‘You don’t understand how hypothesis testing works,’” Bootheway said.
Bootheway explains the reason behind the inaccurate analyses of the test.
“Their ignorance of the procedure is causing them to ask the wrong question or demand the wrong answer,” Bootheway said of researchers who were inappropriately interpreting the procedure.
Bootheway said he is currently working on another paper on the same subject. The second paper will focus more on the interplay between “statistical power” and “statistical severity.”
