## Quantifying ArchaeologyQuantitative reasoning is central to archaeology: quantitative methods are a vital part of every archaeologist's mental tool kit. This new edition of Stephen Shennan's extremely popular textbook introduces students to the basic quantitative methods used within the discipline as well as some of the more advanced methods. Shennan explains the relevant areas of statistics in terms easily assimilated by archaeology students; instead of introducing statistics as it is taught in other disciplines, he draws his working examples from archaeological sources. Exercises at the end of each chapter also directly relate to issues likely to arise within the study of archaeology. |

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### Contents

Picture Summaries of a Single Variable | 21 |

Numerical Summaries of a Single Variable | 34 |

An Introduction to Statistical Inference | 48 |

Estimation and Testing with the Normal Distribution | 71 |

The ChiSquared Test and Measures of Association | 104 |

When the Regression Doesnt Fit | 151 |

Classification and Cluster Analysis | 216 |

Multidimensional Spaces and Principal | 265 |

Correspondence Analysis and Other Multivariate | 308 |

Probabilistic Sampling in Archaeology | 361 |

401 | |

Appendix | 407 |

424 | |

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### Common terms and phrases

archaeological area of available artefacts assemblages associated assumptions available land average axes axis burials burins calculated chapter chi-squared cluster analysis cluster sampling CM CM CM columns confidence interval correlation coefficient corresponding data points defined degrees of freedom density described dimensions distance estimate example expected values formula given grave grave-pit height hoards independent variables individual inertia involved large number level of measurement lithic look matrix measure median mesolithic methods microliths multiple regression normal distribution null hypothesis number of observations obtain overall palstaves particular patterning plot population posthole pottery quantity principal components principal components analysis proportion randomisation regression line relationship represent residuals result scale scattergram scrapers sherds shown in Figure significance similarity simple random sample simply soil type square standard deviation standard error standardised statistical Table techniques test-pit tion total number variance variation vessels