College and university buildings are usually named after the individual(s) who provide all or most of the money needed to design and build them. On rare occasions, however, a building is named in honor of a professor. That’s the case with the Lindquist Center at the University of Iowa. It is named after E. F. Lindquist, a teacher and scholar who made major contributions to the fields of statistics and testing.
In one of the books Lindquist authored, he provided some sage advice to those who analyze data with statistical tools and to those who read or hear the research-based claims made by those who have analyzed data statistically. Here is what Lindquist said:
“Sound statistical judgment involves a keen appreciation of the inherent LIMITATIONS of statistical techniques and of the original data to which they are applied. In the derivation of these techniques, assumptions are frequently made which cannot be satisfied completely in practical applications. The failure to satisfy these conditions necessitates many qualifications in the interpretations of the results obtained.”
In the middle sentence of this passage, notice that Lindquist points out that important assumptions (concerning data and analytic tools) frequently are not satisfied in studies conducted out in the “real world.” As a consequence of these assumptions being violated, Lindquist then asserts, research findings need to be qualified. Being aware of the LIMITATIONS of statistics, he argues, is necessary for sound statistical judgment.
Unfortunately, many applied researchers who publish research reports based on the statistical analysis of numerical data pay little or no attention to the limitations of their data and of the statistical tools they use. Theoretically, the review process used by good journals is supposed to prevent the publication of articles lacking the “sound statistical judgment” called for by Lindquist. In practice, however, not-so-good articles sometimes slip through the review process.
When reading or listening to the summary of a statistically-based research investigation, be vigilant and try to discern whether or not the researcher(s) who conducted the investigation used what Lindquist referred to as “sound statistical judgment.” If so, be more inclined to be influenced by the study’s finding(s). If not, resist the temptation to believe all you read or hear simply because it’s a summary of research.