In the last century, many vision scientists have considered individual variability in data to be “error,” thus overlooking a trove of systematic variability that reveals sensory, cognitive, neural and genetic processes. This “manifesto” coincides with old and recent prescriptions of a covariance-based methodology for vision. But the emphasis here is on using small samples to both discover and confirm characteristics of visual processes, and on reanalyzing archival data. This presentation reviews, briefly, 215 years of sporadic and often neglected research on normal individual variability in vision (including 25+ years of my own research). It reviews how others and I have harvested covariance to a) develop computational models of structures and processes underlying human and animal vision, b) analyze and delineate the developing visual system, c) compare typical and abnormal visual systems, d) relate visual behavior, anatomy, physiology and molecular biology, e) interrelate sensory processes and cognitive performance, and f) develop efficient (non-redundant) tests. Some examples are from my factor-analytic research on spatiotemporal, chromatic, stereoscopic, and attentional processing.