Sampled to Death? The Rise and Fall of Probability Sampling in Archaeology

Abstract

After a heyday in the 1970s and 1980s, probability sampling became much less visible in archaeological literature as it came under assault from the post-processual critique and the widespread adoption of “full-coverage survey.” After 1990, published discussion of probability sampling rarely strayed from sample-size issues in analyses of artifacts along with plant and animal remains, and most textbooks and archaeological training limited sampling to regional survey and did little to equip new generations of archaeologists with this critical aspect of research design. A review of the last 20 years of archaeological literature indicates a need for deeper and broader archaeological training in sampling; more precise usage of terms such as “sample”; use of randomization as a control in experimental design; and more attention to cluster sampling, stratified sampling, and nonspatial sampling in both training and research.

Beyond dots with dates: A landscape approach to the Sohar hinterlands

“…Landscape archaeology, defined as a type of research based on systemic surface survey and that results in quantifiable datasets of high quality (Banning, 2002(Banning, , 2021, has started to be practiced in southeastern Arabia only in recent years. While in other parts of Western Asia landscape archaeology has established itself as an important method for mapping archaeological remains from the 1960s onwards and analysis has shifted to the longue durée changes in particular landscapes and the comparative assessment of trajectories or (de)urbanisation across regions (Barker et al, 2007;Wilkinson et al, 2014), the situation in southeastern Arabia is markedly different.…”

Characterising the stone artefact raw materials at Liang Bua, Indonesia

“…As such, we opted for an opportunistic survey approach guided by local community members. We recognise that, unlike probabilistic or systematic sampling (Banning,[4]), this survey approach carries inherent bias, such that the survey outcome is in no way representative of the overall raw material distribution. However, given the limited prior information regarding the raw materials, especially for chert, as well as other logistical constraints, including very poor surface visibility due to dense vegetation cover, relying on local community knowledge was the best solution to obtain the samples for our study purposes.…”

(DIGSS) Determination of Intervals using Georeferenced Survey Simulation: An R package for subsurface survey

“…In spite of immense advances in the speed and power of personal computers in the ensuing decades, we are aware of only a handful of recent attempts [ 10 – 14 ] that use modern computing power in further service of this issue. Whether the dearth of studies in the 1990s and early 2000s is a consequence of the “Post-Processual Critique” or the rise of so-called “full-coverage” survey approach, as Banning [ 15 ] suggests for probability sampling approaches in archaeology more broadly, is unknown.…”