Information identified as archived is provided for reference, research or recordkeeping purposes. It is not subject to the Government of Canada Web Standards and has not been altered or updated since it was archived. Please contact us to request a format other than those available.
The 2006 Census required the participation of the entire population of Canada, over 31 million people distributed over a territory of 9 million square kilometres. Although there are high quality standards governing the collection and processing of the data, it is not possible to eliminate all errors. In order to help users assess the usefulness of census data for their purposes, the 2006 Census Technical Reports detail the conceptual framework and definitions used in conducting the census, as well as the data collection and processing procedures employed. Also, the principal sources of error, including, where possible, the size of these errors, are also described, as are any unusual circumstances which might limit the usefulness or interpretation of census data. With this information, users can determine the risks involved in basing conclusions or decisions on census data.
This 2006 Census Technical Report deals with the method of sampling and weighting used in the 2006 Census as well as its effect on the results. Due to the fact that some information is collected on a sample basis and weighted to the full population level, bias and discrepancies can be observed in the final estimates. This report identifies these observed differences and explains the probable causes. This report has been prepared by Wesley Benjamin, Darryl Janes, and Mike Bankier, with the support of staff from two divisions in Statistics Canada: the Social Survey Methods Division and the Census Operations Division.
Sampling is an accepted practice in many aspects of life today. The quality of produce in a market may be judged visually by a sample before a purchase is made; we form opinions about people based on samples of their behaviour; we form impressions about countries or cities based on brief visits to them. These are all examples of sampling in the sense of drawing inferences about the 'whole' from information for a 'part.'
In a more scientific sense, sampling is used, for example, by accountants in auditing financial statements, in industry for controlling the quality of items coming off a production line, and by the takers of opinion polls and surveys in producing information about a population's views or characteristics. In general, the motivation to use sampling stems from a desire either to reduce costs or to obtain results faster, or both. In some cases, measurement may destroy the product (e.g., testing the life of light bulbs) and sampling is therefore essential. A disadvantage of sampling is that the results based on a sample may not be as precise as those based on the whole population. However, when the loss in precision (which may be quite small when the sample is large) is tolerable in terms of the uses to which the results are to be put, the use of sampling is often cost-effective.
The 2006 Census of Population made use of sampling in a variety of ways. It was used in ensuring that the quality of the enumerator's work in collecting questionnaires met certain standards; it was used in the control of the quality of coding responses during processing; it was used in estimating both the amount of undercoverage and the amount of overcoverage; it was used in evaluating the quality of census data. However, the primary use of sampling in the census was during the field enumeration when all but the basic census data were collected only from a sample of households. This report describes this last use of sampling and evaluates the effect of sampling on the quality of census data.
Chapters 1 and 2 describe the data collection and data processing procedures. Chapter 3 reviews the history of the use of sampling in Canadian censuses and describes the sampling procedures used in the 2006 Census. Chapter 4 explains the procedures used for weighting up the sample data to the population level and provides operational and theoretical justifications for these procedures. In Chapter 5 an overview of the studies designed to evaluate the 2006 Census sampling and weighting procedures is presented, while Chapters 6, 7, 8 and 9 present the results of these studies. Chapter 10 presents some conclusions on the weighting procedures used in 2006.