By James A. Moore, Arthur S. Keene
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Extra info for Archaeological Hammers and Theories
These applications were quite frequently accompanied by attempts to evaluate the utility of sampling for the estimation and specification of archaeological distributions. Examples include sample surveys in the Rio Grande Valley (Judge 1973; Judge et al. 1975), Elk Ridge (DeBloois 1975), Cedar Mesa (Matson and Lipe 1975), central Arizona (Mueller 1974), Cache River, where only plowed fields were surveyed (Schiffer and House 1975), Reese River (Thomas 1972, 1973) and others. These surveys shared a number of features: (1) restricted time, money, and personnel made sampling unavoidable; (2) sampling designs were stratified according to the judicious use of prior knowledge about regional environments and cultural behaviors; (3) there was usually some sort of multistage survey strategy in which limited sampling was carried out to get a rough idea about the sampled area; followed by (4) a set of in- 48 H.
Isaac, Z. Kaufulu, E. Kroll, K. Schick, N. Toth, and A. K. Behrensmeyer 1980 Fxjj50: an early Pleistocene site in northern Kenya. World Archaeology 12: 109-136. , L. H. Keeley, and F. L. Van Noten 1979 Stone tools, toolkits, and human behavior in prehistory. Current Anthropology 20:661-683. Chilcott, J. , and J. J. Deetz 1964 The construction and uses of a laboratory archaeological site. American Antiquity 29:328-337. Clarke, D. L. 1973 Archaeology: the loss of innocence. Antiquity 47:6-18. DeBoer, W.
Corresponding to changing observations per unit space or volume, this mathematical construct will have peaks, valleys, and other "topographic" features much like a real three-dimensional landscape. A given distribution can be said to be fully specified, if our model of it satisfactorily retrodicts our observations and concisely anticipates those possible observations that have not yet been collected. Short of actually gathering all possible observations, four different scientific tasks help us in developing satisfactory approximations of distributional shape: prospecting, sampling, estimation, and hypothesis testing.