List of Statistical Tables

Note: The raw data in these tables are obtained by straight counts of occurrences of a code from the Gazetteer. The incidence of a characteristic is only counted once for any site in each period. For example, if a site in 3500-2500bc contains more than one identifiable male burial, it is the incidence of evidence for male burial on the site that is counted and not the number of males buried: code 5101 thus means 'evidence for male burial' and holds no connotation of quantity. The same applies to all other incidences of any characteristic. The raw data are therefore not weighted by times of occurrence. Gazetteer sites 1 - 1699 are included in these statistical analyses; sites 1700 - 1710 were added later in the study.

Disposal Locations

Monument Characteristics

Monument Orientation

Body Orientation


Disposal Method

Sex Incidence

Burial Groups


Personal Grave Goods

Animal Associations

Domestic Refuse

Single and Multiple Disposal

Physical Burial Containers

Summary Table of Numbers of Sites by Period
Some sites have evidence in several periods, and hence the total number of individual site locations is exceeded

AREASTotal sites3500-25002500-14001400-800800-100100-AD43

Statistical comment: The tables were considered for the application of Chi-squared tests for statistical significance, but less than a dozen contain data that meet the requirements for such tests, mainly because either the numbers in the cells are too small or the characteristics are not mutually exclusive in a table. However, Chi-tests are intended for samples of data, to test whether the results might be interpreted as significant for the whole (unknown) set. This Gazetteer is more by nature of a census (as many sites again without good data being rejected for inclusion), and therefore what is recorded is an effort to include the whole.

A more useful statistical test would have been one that took combinations of characteristics, and divined which were in significant inter-relationships. This might separate the data more effectively, a task undertaken by more intuitive methods relying on the normalising tables (the third in each set of three) as a check.


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