Applied Probability
Despite the fears of university mathematics departments, mathematics educat,ion is growing rather than declining. But the truth of the matter is that the increases are occurring outside departments of mathematics. Engineers, computer scientists, physicist
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Preface to the First Edition When I was a postdoctoral fellow at UCLA more than two decades ago, I learned genetic modeling from the delightful texts of Elandt-Johnson [2] and Cavalli-Sforza and Bodmer [1]. In teaching my own genetics course over the past few years, first at UCLA and later at the University of Michigan, I longed for an updated version of these books. Neither appeared and I was left to my own devices. As my hastily assembled notes gradually acquired more polish, it occurred to me that they might fill a useful niche. Research in mathematical and statistical genetics has been proceeding at such a breathless pace that the best minds in the field would rather create new theories than take time to codify the old. It is also far more profitable to write another grant proposal. Needless to say, this state of affairs is not ideal for students, who are forced to learn by wading unguided into the confusing swamp of the current scientific literature. Having set the stage for nobly rescuing a generation of students, let me inject a note of honesty. This book is not the monumental synthesis of population genetics and genetic epidemiology achieved by Cavalli-Sforza and Bodmer. It is also not the sustained integration of statistics and genetics achieved by Elandt-Johnson. It is not even a compendium of recommendations for carrying out a genetic study, useful as that may be. My goal is different and more modest. I simply wish to equip students already sophisticated in mathematics and statistics to engage in genetic modeling. These are the individuals capable of creating new models and methods for analyzing genetic data. No amount of expertise in genetics can overcome mathematical and statistical deficits. Conversely, no mathematician or statistician ignorant of the basic principles of genetics can ever hope to
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