unvarying throughout a person’s life. Changes in health, periods of illness, crisis, activity level, work schedule, and so forth, are said not to influence biorhythms.
It is largely this unvarying nature of the alleged biorhythms that makes them so easy to reckon. To calculate an individual’s position on any of the three biorhythms on a given date, all one has to know is the person’s birth date and the date for which the calculation is to be made. One then figures out how many days the person has lived until the day in question; that number is divided by twenty-three, twenty-eight, or thirty-three, depending on which biorhythm one is interested in. The remainder gives the person’s position in the biorhythm cycle on the day in question.
The evidence put forth by biorhythm proponents for the existence of these rhythms offers some classic examples of pseudoscientific thinking. The commonest ploy is to present lists of terrible things (like dying) that happened to people when they were on the down side of one or more of the rhythms. Airline crashes are favored by biorhythm proponents, who take joy revealing that the pilot, copilot, navigator, or a flight attendant was on a critical day of one or more of the three rhythms, or low on one or more of the three rhythms, the day the plane crashed. Of course, there have been a fair number of plane crashes and other disasters over the past century, so it’s not hard to find someone somehow associated with the disaster who was having a biorhythmically down or critical day at the time of the disaster. Similarly, lists of wonderful things (pitching a no-hitter, winning a boxing match, and so forth) that have happened to people when they were on the up phase of one or more of their biorhythms are presented as further proof of the validity of the theory.
Such lists are highly selective reporting and prove nothing. If one believed that, for example, accidents and disasters were more likely to occur on odd-numbered Thursdays that fell on even-numbered dates in years that end in odd numbers, one could probably come up with quite a list of accidents “proving” that danger lurks on such days. In fact, two minutes of looking through the
Further examination of the dates of disasters reveals many that took place on days other than Thursday, let alone a Thursday with the special characteristics noted above. But if one were writing a book to convince people that certain types of Thursdays were dangerous, or trying to sell a consulting service based on that premise, one certainly wouldn’t mention all the accidents that took place when the theory predicts they shouldn’t have. Similarly, you’ll never read in books written by biorhythm proponents about the thousands of events, good and bad, that took place when biorhythm theory predicted they shouldn’t. Many of these promoters have financial stakes in the theory’s validity. For example, Bernard Gittelson, author of the most popular book on biorhythm theory, first published in 1975, ran a biorhythm computer and consulting service in which he advised companies on how to schedule their employees according to their biorhythms. Another biorhythm author, Vincent Mallardi (1978), also ran a biorhythm consulting business.
The real question regarding the relationship between accidents (or other events) and critical days is whether more accidents occur on critical days than expected by chance. Since critical days make up 20 percent of all days (20.4 percent, to be exact), if biorhythms really exist and influence behavior, more than 20.4 percent of accidents will occur on critical than on noncritical days. That is, if biorhythm theory is false, about 20 percent of all accidents occur on critical days. Hines (1998) reviewed 132 published studies of biorhythm theory. Among these were studies that examined more than twenty-five thousand accidents for biorhythm effects. In that vast number of automobile, aircraft, and industrial accidents, there was not even a hint of any biorhythm effect, even when those accidents not clearly due to human error were excluded from consideration. Many other variables have been examined for biorhythm effects. Hines provided a detailed review of these studies so it will suffice to indicate here that studies of sports performance of various types, reaction times, intelligence test performance, fluctuation in human moods and emotions, days of death of large samples of individuals, days on which women give birth and the sex of their children, and classroom tests have all failed to reveal any biorhythmic effect.
Given these overwhelmingly negative results, which had emerged by the late 1970s, it is easy to see why interest in further testing of biorhythm theory has waned in recent years. However, a few studies reviewed by Hines (1998) should be mentioned. One is particularly interesting in that it seems to give strong support to biorhythm theory. Latman (1977) studied 260 motor vehicle accidents and found that 37 percent of them occurred on critical days, a figure significantly higher than the 20 percent expected by chance. Since this study was well done and free of the common statistical errors found in some studies claiming to support biorhythm theory, it seemed to provide the first good evidence in favor of the theory. However, in a later study, Latman and Garriott (1980) reported that these initial positive findings had been the result of an unexpected source of error. Latman had used a “Biomate” brand biorhythm calculator to determine the biorhythmic position of the individuals involved in the traffic accidents. Further study showed that this brand of biorhythm calculator miscalculates biorhythms such that the number of critical days comes out as 37 percent instead of the correct 20 percent. When Latman and Garriott reexamined Latman’s data using accurate methods for determining individuals’ biorhythmic position, all signs of any biorhythm effect vanished.
Other studies have been entirely negative in regard to biorhythm theory. Wood, Krider, and Fezer (1979) studied seven hundred accidents that brought their victims to the local emergency room, and found no biorhythmic effects. Dezeisky and Toohey (1978) found the date of suicides unrelated to the suicides’ biorhythmic position. Hunter and Shane (1979) and Feinleib and Fabsitz (1978) found no biorhythm effect on the day of death. Englund and Naitoh (1980) found no effect on classroom quiz scores of college students or on the landing performance of experienced Navy pilots. Reilly, Young, and Seddon (1983) found no biorhythm effects on the “best performances in 610 top ranked European female track and field specialists over a single competitive season” (p. 215). James (1984) found no biorhythm effect on a major test of academic performance taken by 368 students or on a test of psychoneurotic tendencies given to 338 students. The results of the studies now in the literature are clear: biorhythms do not exist.
It is important to ask why biorhythm theory became so popular in the first place. What was the nature of the evidence that convinced so many people that there was something to the theory? As mentioned above, a major source of support was lists of events that seemed to confirm the theory. This type of useless data no doubt convinced many. However, proponents of biorhythm theory also allude to various scientific studies that are said to show either that using biorhythm theory reduces a company’s accident rate or that about 60 percent of a firm’s accidents take place on critical days. Thus, both Gittelson (1982) and Thommen (1973) mention several Japanese transportation firms that allegedly have used and studied biorhythm theory. Unfortunately, no references are given for the studies cited, and attempts to confirm that the studies were actually conducted or that the firms in question use biorhythm theory have always been fruitless. This sort of study can best be referred to as phantom studies, as they seem simply not to exist. This has not prevented biorhythm proponents from quoting them to increase sales of their books and services.
A second type of study said to support biorhythm theory turns out, upon inspection, to suffer from fatal statistical flaws, often because the author had little idea how to carry out a correct statistical analysis. One particular flaw is most common and concerns the method used to determine which day is critical. As mentioned earlier, critical days account for about 20 percent of all days. But it is not always clear, according to biorhythmists, exactly which day is critical for an individual. What if someone is born at 11:58 P.M.? Or 12:01 A.M.? Williamson (1975) points out that “an individual born shortly following midnight is biorhythmically closer to the preceding day than an individual born at noon. Similarly, an individual born approaching midnight is closer to the coming day” (p. 18). To get around this problem, in his study of helicopter accidents, Williamson tallied as falling on a critical day any accident that fell on the calculated critical day, the day before, or the day after. Naturally, if you add in the days before and after the critical day, you are now defining 60 percent of all days as “critical” (20 percent x 3). With such a definition, one would need to find that significantly more than 60 percent of a sample of accidents fell on the critical day, plus and minus one. Williamson fails to realize this, however, and claims that his finding that 58 percent of the accidents in his sample fell on critical days (as he defined them) is strongly supportive of biorhythm theory, since 58 percent is clearly greater than 20 percent. Pittner and Owens (1975) make the same error in their study.
Another statistical error, occurring either in the authors’ interpretation of their own data or in biorhythm proponents’ interpretation of others’ data, can be termed the “shotgun” approach. Thus, Knowles and Jones (1974) studied police-suspect altercations as a function of the biorhythmic position of both individuals. It is not clear from
