Modern molecular genetics research has provided biologists and epidemiologists with a number of laboratory protocols and assays that can be used to investigate the genetic basis of traits and diseases of all types. In fact, these tools have been used by statistically-minded geneticists with great success in the isolation of genes that determine simple, but devastating, Mendelian diseases such as cystic fibrosis and neurofibromatosus. Simple Mendelian traits and diseases, however, are the exception rather than the rule in nature. Much more common are traits and diseases that are much more complex in that they are determined by numerous genetic and non-genetic factors, making the isolation of each and every one of them difficult simply because the influence of any one particular factor might be obscured or masked by the others. One particularly difficult class of complex traits to assess genetically are "quantitative" traits, or traits that exhibit continuous or metrical variation in the population at large. The difficulties that quantitative traits present to the genetics researcher stem both from their multifactorial bases as well as from inherent difficulties in modeling them for analysis purposes. This book describes statistical modeling and analysis approaches for dissecting the genetic basis of human quantitative traits, such as blood pressure, height, and cholesterol level, and focuses primarily on the identification of genes that influence quantitative traits through the use of modern DNA marker and sequencing technologies. It is written for upper undergraduate and graduate students, applied geneticists and clinical researchers, epidemiologists, specialists in the field, and anyone with a will or inclination to understand how one can approach the characterization of the genetic basis of human quantitative traits and diseases.