If I want to build a house, wouldn't it be wise to learn carpentry? Does the analogy hold for data-analytic multivariate models? Or is it simply enough to let a machine do it, with no knowledge by the machine operator of how to interpret the results from those modeling efforts? Or is it true, as one person has recently asserted, that he could replicate ALL statistical procedures and techniques using MapReduce, without knowing anything about statistics and probability, or the vast collection of discipline-specific applications of statistical science in economics, the social sciences, the physical sciences, (including physics and chemistry itself), business or organizational management, archaeology, anthropology, and other historical sciences (evolutionary biology and genetics), and biostatistics, to name a few? Will machine learning supplant all of these careful developed approaches to problems that are peculiar or particular to a very large array of efforts aimed at scientific advance?