Olorgesailie.sub {archdata}

Stone tool subclasses, Olorgesailie, Kenya

Description

The data represent the number of specimens in each of 16 artifact subclasses recovered from 19 localities at the Lower Paleolithic site of Olorgesailie as described in Isaac (1977).

Usage

data(Olorgesailie.sub)

Format

A data frame with 19 observations showing the stratum, locality and the number of specimens for each of 16 stone artifact types.

Strat

stratum: Lower, Middle, Upper

Locality

Locality

HA

Number of handaxes

PHA

Number of pick-like handaxes

CHA

Number of chisel handaxes

CL

Number of cleavers

KN

Number of knives

BLCT

Number of broken large cutting tools

PAT

Number of picks and trièdres

CH

Number of choppers

CS

Number of core scrapers

LFS

Number of large flake scrapers

CB

Number of core bifaces

OLT

Number of other large tools

SSS

Number of small scrapers simple

SSNP

Number of small scrapers nosed point

OST

Number of other small tools

SP

Number of spheroids

Details

The data come from Table E1 in Isaac (1977: 239). The Locality contains the column headings in the original table. The rownames are the same as those in Olorgesailie.maj. The attribute Variables in the data frame includes the full variable names. Potts (2011) provides updated information on the site complex.

Source

Isaac, Glynn Ll. 1977. Olorgesailie: Archeological Studies of a Middle Pleistocene Lake Basin in Kenya. The University of Chicago Press.

References

Carlson, David L. 2017. Quantitative Methods in Archaeology Using R. Cambridge University Press, pp 280-293.

Potts, R. 2011. Olorgesailie–Retrospective and current synthesis. In Casting the net wide: papers in honor of Glynn Isaac and his approach to human origins research, edited by J. Sept and D. Pilbeam, pp 1–20. American School of Prehistoric Research Monographs in Archaeology and Paleoanthropology.

Examples

data(Olorgesailie.sub)
# Chi square after removing the first two columns and simulating the p
# value since there are a number of very small expected values
chisq.test(Olorgesailie.sub[,3:18], simulate.p.value=TRUE)
# Compute percentages over the localities
Olor.pct <- prop.table(as.matrix(Olorgesailie.sub[,3:18]), 1)*100
boxplot(Olor.pct, cex.axis=.7)