## Applied ProbabilityDespite 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, physicists, chemists, economists, statis- cians, biologists, and even philosophers teach and learn a great deal of mathematics. The teaching is not always terribly rigorous, but it tends to be better motivated and better adapted to the needs of students. In my own experience teaching students of biostatistics and mathematical bi- ogy, I attempt to convey both the beauty and utility of probability. This is a tall order, partially because probability theory has its own vocabulary and habits of thought. The axiomatic presentation of advanced probability typically proceeds via measure theory. This approach has the advantage of rigor, but it inwitably misses most of the interesting applications, and many applied scientists rebel against the onslaught of technicalities. In the current book, I endeavor to achieve a balance between theory and app- cations in a rather short compass. While the combination of brevity apd balance sacrifices many of the proofs of a rigorous course, it is still cons- tent with supplying students with many of the relevant theoretical tools. In my opinion, it better to present the mathematical facts without proof rather than omit them altogether. |

### What people are saying - Write a review

We haven't found any reviews in the usual places.

### Other editions - View all

### Common terms and phrases

algorithm alignment allele frequencies Amer J Hum apply approximation autosomal base binomial calculation cell Chapter Chen-Stein chiasma chromosome clone codon column components compute condensed identity conditional Consider corresponding counts covariance deﬁne defined denote density descent graph descent tree distance EM algorithm entries equilibrium distribution expected number exponential Figure ﬁrst formula founder gene gamete geneticists genotype given haplotype Hardy-Weinberg equilibrium Hint Hum Genet human independent inequality interval kinship coefficient Lange linkage equilibrium location scores loci locus loglikelihood marker locus Markov chain mathematical matrix maximum likelihood estimates maximum parsimony method nodes obligate breaks observed p-value pairs parameters parents pattern pedigree phenotypes Poisson polygenic population positive posterior probability problem protein radiation hybrid random variable randomly recombination fraction recurrence sample sequence statistic stochastic Suppose Table tion trait transition typed update variance vector Zmax