William Sealy Gosset and William A. Silverman: two "students" of science

In 1908, William Sealy Gosset, a chemist in an Irish brewery, published his second article on statistics in Biometrika under the pseudonym "Student." He chose this pseudonym because his company did not allow its scientists to publish confidential data. In the article, Gosset described a procedure to assess population means by using small samples. This was the origin of the "Student's t test." Dr William Silverman (1917-2004), a pioneer neonatologist, also used the pseudonym "Student." He sent thousands of notes, clippings, anecdotes, and quotations to Pediatrics with the signature line "Submitted by Student" that appeared as blurbs at the ends of articles since 1977. Both Gosset and Silverman were rigorous students of science. Silverman chose pseudonyms to seek readers' responses to the message rather than the messenger. He also wished that one would remain a perpetual student, ready to say "I don't know," and strive to understand the human side of medicine. This brief article provides a perspective on these 2 "students" of science.

Who was student and why do we care so much about his t-test?

Statistics is the study of populations, how they relate to one another and what effect sampling has in terms of representing the original population. Use of statistical tools has been facilitated by modern computer technology; however, given the ease in which results are obtained, it is easy to overlook potentially incorrect use of the various statistical tests. Statistical tools are invaluable for investigators because they make it possible to determine if scientific results are important. When a test is used, it is important to know that the result of any statistical test is valid to avoid erroneous conclusions. To do so, the investigator must have a basic understanding of the test's assumptions and limitations. Modern statistical packages often include a variety of results relating to the test's applicability to the data analyzed. Not uncommonly, biologists are unfamiliar with these analyses. This review intends to improve the reader's understanding of t-tests by providing a history of Student's t-test, and its assumptions, applications, and limitations. Part 1 of the series ("The Mean and Standard Deviation: What Does It All Mean?") reviewed basic aspects of distributions, measures of central tendency, and dispersion assessment. Small sample size effects on accurate estimation of a population mean and group comparisons for continuous data are presented in this review.