Abstract
It is shown in this analysis that the distribution of human ovulatory cycles can be described based upon one simple assumption. This assumption is that the random variable underlying ovulation is the follicle development rate. Previous attempts to describe variability in ovulation cycles have assumed that the measured time interval was the random variable. The assumption that the random variable is the rate rather than the time, leads mathematically to the observed skew towards longer ovulatory cycles. The resultant distribution model is shown to agree with observed variability patterns for the preovulatory phase, the postovulatory phase and overall menstrual cycle.
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