Keyword search

Filter results by

Search Help
Currently selected filters that can be removed

Keyword(s)

Geography

1 facets displayed. 0 facets selected.

Content

1 facets displayed. 0 facets selected.
Sort Help
entries

Results

All (143)

All (143) (0 to 10 of 143 results)

  • Articles and reports: 11-522-X202200100004
    Description: In accordance with Statistics Canada’s long-term Disaggregated Data Action Plan (DDAP), several initiatives have been implemented into the Labour Force Survey (LFS). One of the more direct initiatives was a targeted increase in the size of the monthly LFS sample. Furthermore, a regular Supplement program was introduced, where an additional series of questions are asked to a subset of LFS respondents and analyzed in a monthly or quarterly production cycle. Finally, the production of modelled estimates based on Small Area Estimation (SAE) methodologies resumed for the LFS and will include a wider scope with more analytical value than what had existed in the past. This paper will give an overview of these three initiatives.
    Release date: 2024-03-25

  • Articles and reports: 11-522-X202200100006
    Description: The Australian Bureau of Statistics (ABS) is committed to improving access to more microdata, while ensuring privacy and confidentiality is maintained, through its virtual DataLab which supports researchers to undertake complex research more efficiently. Currently, the DataLab research outputs need to follow strict rules to minimise disclosure risks for clearance. However, the clerical-review process is not cost effective and has potential to introduce errors. The increasing number of statistical outputs from different projects can potentially introduce differencing risks even though these outputs from different projects have met the strict output rules. The ABS has been exploring the possibility of providing automatic output checking using the ABS cellkey methodology to ensure that all outputs across different projects are protected consistently to minimise differencing risks and reduce costs associated with output checking.
    Release date: 2024-03-25

  • Articles and reports: 11-522-X202200100009
    Description: Education and training is acknowledged as fundamental for the development of a society. It is a complex multidimensional phenomenon, which determinants are ascribable to several interrelated familiar and socio-economic conditions. To respond to the demand of supporting statistical information for policymaking and its monitoring and evaluation process, the Italian National Statistical Institute (Istat) is renewing the education and training statistical production system, implementing a new thematic statistical register. It will be part of the Istat Integrated System of Registers, thus allowing relating the education and training phenomenon to other relevant phenomena, e.g. transition to work.
    Release date: 2024-03-25

  • Articles and reports: 45-20-00022023004
    Description: Gender-based Analysis Plus (GBA Plus) is an analytical tool developed by Women and Gender Equality Canada (WAGE) to support the development of responsive and inclusive initiatives, including policies, programs, and other initiatives. This information sheet presents the usefulness of GBA Plus for disaggregating and analyzing data to identify the groups most affected by certain issues, such as overqualification.
    Release date: 2023-11-27

  • Journals and periodicals: 12-206-X
    Description: This report summarizes the annual achievements of the Methodology Research and Development Program (MRDP) sponsored by the Modern Statistical Methods and Data Science Branch at Statistics Canada. This program covers research and development activities in statistical methods with potentially broad application in the agency’s statistical programs; these activities would otherwise be less likely to be carried out during the provision of regular methodology services to those programs. The MRDP also includes activities that provide support in the application of past successful developments in order to promote the use of the results of research and development work. Selected prospective research activities are also presented.
    Release date: 2023-10-11

  • Surveys and statistical programs – Documentation: 84-538-X
    Geography: Canada
    Description: This electronic publication presents the methodology underlying the production of the life tables for Canada, provinces and territories.
    Release date: 2023-08-28

  • Surveys and statistical programs – Documentation: 32-26-0006
    Description: This report provides data quality information pertaining to the Agriculture–Population Linkage, such as sources of error, matching process, response rates, imputation rates, sampling, weighting, disclosure control methods and data quality indicators.
    Release date: 2023-08-25

  • Stats in brief: 98-20-00032021012
    Description: This video builds on concepts introduced in the other videos on income. It explains key low-income concepts - Market Basket Measure (MBM), Low income measure (LIM) and Low-income cut-offs (LICO) and the indicators associated with these concepts such as the low-income gap and the low-income ratio. These concepts are used in analysis of the economic well-being of the population.
    Release date: 2023-03-29

  • Stats in brief: 98-20-00032021017
    Description: This video will help you understand the concept of first official language spoken. It explores the usefulness and relevance of the first official language spoken and how it is developed, disseminated and analyzed. You will also learn how the concept of first official language spoken takes into account knowledge of both official languages, mother tongue and language spoken most often at home.
    Release date: 2023-03-29

  • Data Visualization: 71-607-X2020010
    Description: The Canadian Statistical Geospatial Explorer empowers users to discover geo enabled data holdings of Statistics Canada at various levels of geography including at the neighbourhood level. Users are able to visualize, thematically map, spatially explore and analyze, export and consume data in various formats. Users can also view the data superimposed on satellite imagery, topographic and street layers.
    Release date: 2023-01-24
Data (8)

Data (8) ((8 results))

  • Data Visualization: 71-607-X2020010
    Description: The Canadian Statistical Geospatial Explorer empowers users to discover geo enabled data holdings of Statistics Canada at various levels of geography including at the neighbourhood level. Users are able to visualize, thematically map, spatially explore and analyze, export and consume data in various formats. Users can also view the data superimposed on satellite imagery, topographic and street layers.
    Release date: 2023-01-24

  • Public use microdata: 56M0001X
    Description:

    Statistics Canada was approached by Stentor Resource Centre Incorporated to conduct a survey to monitor the telephone penetration rates across Canada. The survey determines if the respondents have a telephone line in their residence. If they do not have a telephone line, information is collected as to the reasons why. Information is also collected on the income characteristics of the selected households.

    The management of the survey was transferred from Stentor to Bell Canada in the Fall of 1998.

    The Labour Force Survey (LFS) supplementary capacity is used to conduct this biannual survey. A sample of approximately 44,000 respondents is used for this survey (five out of six rotation groups). The survey data are collected using Computer Assisted Interviewing (CAI). The first data collection procedure took place during November's LFS week in 1996.

    This microdata file is prepared biannually and contains the variables from the survey, plus geographical variables from the LFS (province, census metropolitan area, urban/rural breakdown). No other variables from the LFS are added to the file.

    Release date: 2014-12-12

  • Public use microdata: 82M0011X
    Description:

    The main objective of the 2002 Youth Smoking Survey (YSS) is to provide current information on the smoking behaviour of students in grades 5 to 9 (in Quebec primary school grades 5 and 6 and secondary school grades 1 to 3), and to measure changes that occurred since the last time the survey was conducted in 1994. Additionally, the 2002 survey collected basic data on alcohol and drug use by students in grades 7 to 9 (in Quebec secondary 1 to 3). Results of the Youth Smoking Survey will help with the evaluation of anti-smoking and anti-drug use programs, as well as with the development of new programs.

    Release date: 2004-07-14

  • Public use microdata: 81M0013X
    Description:

    The Adult Education and Training Survey (AETS) is Canada's most comprehensive source of data on individual participation in formal adult education and training. It is the only Canadian survey to collect detailed information about the skill development efforts of the entire adult Canadian population. The AETS provides information about the main subject of training activities, their provider, duration and the sources and types of support for training. Furthermore, the AETS allows for the examination of the socio-economic and demographic profiles of both training participants and non-participants. This survey also identifies barriers faced by individuals who wish to take some form of training but cannot. The AETS was administered three times during the 1990s, in 1992, 1994 and 1998, as a supplement to the Labour Force Survey (LFS).

    The content of the AETS was revised to take into account recommendations coming from consultation exercises. As a result, more than half of the 2003 survey is made up of new questions and the target population has been modified.

    The main objectives are:1) To measure the incidence and intensity of adults' participation in job-related formal training.2) To profile employer support to job-related formal training.3) To analyze the aspects of job-related training activities such as: training provider, expenses, financial support, motivations, outcomes and difficulties experienced while training.4) To identify the barriers preventing individuals from participating in the job-related formal training they want or need to take.5) To identify reasons explaining adults' lack of participation and of interest in job-related formal training.6) To relate adults' current participation patterns to their past involvement in and plans about future participation in job-related training.7) To measure the incidence and frequency of adults' participation in job-related informal training.8) To examine the interactions between participation in formal and informal job-related training.

    The population covered by the AETS consists of Canadians 25 years of age and older. This is a change from the population previously targeted by the AETS, which consisted of Canadians aged 17 years of age and older. A primary consideration for this change was the practical difficulties in applying the definition of adult education to individuals in the 17 to 24 years of age group. By definition, adult education excludes students who are still involved in their first or initial stage of schooling. As previous AETS did not precisely identify students still in their initial stage of schooling, analyses using these data had to rely on an ad hoc definition of adult learners. According to this definition, individuals aged 17 to 24 who were not in one of the following situations were excluded from the analysis: full-time students subsidized by an employer and full-time students over 19 enrolled in elementary or secondary programs.

    Release date: 2004-05-27

  • Public use microdata: 12M0013X
    Description:

    Cycle 13 of the General Social Survey (GSS) is the third cycle (following cycles 3 and 8) that collected information in 1999 on the nature and extent of criminal victimisation in Canada. Focus content for cycle 13 addressed two areas of emerging interest: public perception toward alternatives to imprisonment; and spousal violence and senior abuse. Other subjects common to all three cycles include perceptions of crime, police and courts; crime prevention precautions; accident and crime screening sections; and accident and crime incident reports. The target population of the GSS is all individuals aged 15 and over living in a private household in one of the ten provinces.

    Release date: 2000-11-02

  • Public use microdata: 82M0010X
    Description:

    The National Population Health Survey (NPHS) program is designed to collect information related to the health of the Canadian population. The first cycle of data collection began in 1994. The institutional component includes long-term residents (expected to stay longer than six months) in health care facilities with four or more beds in Canada with the principal exclusion of the Yukon and the Northwest Teritories. The document has been produced to facilitate the manipulation of the 1996-1997 microdata file containing survey results. The main variables include: demography, health status, chronic conditions, restriction of activity, socio-demographic, and others.

    Release date: 2000-08-02

  • Public use microdata: 89M0007X
    Description:

    Information in this microdata file refers to survey data collected in September - November, 1994 for persons 15 years of age and older in Canada's ten provinces. The survey's main data objectives were to measure the prevalence and patterns of alcohol and other drug use, to assess harm and other consequences of drug use and to evaluate trends in recent patterns of use. Canada's Alcohol and Other Drugs Survey (CADS) also updates and expands upon data collected in the first survey, the National Alcohol and Other Drugs Survey (NADS), conducted in 1989.

    Release date: 2000-07-07

  • Public use microdata: 82M0008X
    Description:

    The survey, begun in February 1994, monitors the smoking patterns of Canadians over a 12 month period and to measure any changes in smoking resulting from the decrease in taxes in cigarettes which took place in February 1994 in some provinces. It is related to MDF 82M0006. Updates are included in the microdata file price. A guide for this microdata file is available.

    Release date: 1995-06-08
Analysis (109)

Analysis (109) (30 to 40 of 109 results)

  • Articles and reports: 12-001-X201400214092
    Description:

    Survey methodologists have long studied the effects of interviewers on the variance of survey estimates. Statistical models including random interviewer effects are often fitted in such investigations, and research interest lies in the magnitude of the interviewer variance component. One question that might arise in a methodological investigation is whether or not different groups of interviewers (e.g., those with prior experience on a given survey vs. new hires, or CAPI interviewers vs. CATI interviewers) have significantly different variance components in these models. Significant differences may indicate a need for additional training in particular subgroups, or sub-optimal properties of different modes or interviewing styles for particular survey items (in terms of the overall mean squared error of survey estimates). Survey researchers seeking answers to these types of questions have different statistical tools available to them. This paper aims to provide an overview of alternative frequentist and Bayesian approaches to the comparison of variance components in different groups of survey interviewers, using a hierarchical generalized linear modeling framework that accommodates a variety of different types of survey variables. We first consider the benefits and limitations of each approach, contrasting the methods used for estimation and inference. We next present a simulation study, empirically evaluating the ability of each approach to efficiently estimate differences in variance components. We then apply the two approaches to an analysis of real survey data collected in the U.S. National Survey of Family Growth (NSFG). We conclude that the two approaches tend to result in very similar inferences, and we provide suggestions for practice given some of the subtle differences observed.

    Release date: 2014-12-19

  • Articles and reports: 12-002-X201400111901
    Description:

    This document is for analysts/researchers who are considering doing research with data from a survey where both survey weights and bootstrap weights are provided in the data files. This document gives directions, for some selected software packages, about how to get started in using survey weights and bootstrap weights for an analysis of survey data. We give brief directions for obtaining survey-weighted estimates, bootstrap variance estimates (and other desired error quantities) and some typical test statistics for each software package in turn. While these directions are provided just for the chosen examples, there will be information about the range of weighted and bootstrapped analyses that can be carried out by each software package.

    Release date: 2014-08-07

  • Articles and reports: 11F0027M2014089
    Geography: Canada
    Description:

    This paper examines two aspects of productivity growth in Canada's broadcasting and telecommunications industry. The first is the extent to which aggregate MFP growth in the sector came from scale economies as opposed to technical progress. The second is the extent to which aggregate labour productivity growth and MFP growth came from within-firm growth, and from the effect of reallocation due to firm entry and exit and within incumbents' the dynamic forces associated with competitive change.

    Release date: 2014-02-06

  • Articles and reports: 12-001-X201300211871
    Description:

    Regression models are routinely used in the analysis of survey data, where one common issue of interest is to identify influential factors that are associated with certain behavioral, social, or economic indices within a target population. When data are collected through complex surveys, the properties of classical variable selection approaches developed in i.i.d. non-survey settings need to be re-examined. In this paper, we derive a pseudo-likelihood-based BIC criterion for variable selection in the analysis of survey data and suggest a sample-based penalized likelihood approach for its implementation. The sampling weights are appropriately assigned to correct the biased selection result caused by the distortion between the sample and the target population. Under a joint randomization framework, we establish the consistency of the proposed selection procedure. The finite-sample performance of the approach is assessed through analysis and computer simulations based on data from the hypertension component of the 2009 Survey on Living with Chronic Diseases in Canada.

    Release date: 2014-01-15

  • Articles and reports: 12-001-X201300111826
    Description:

    It is routine practice for survey organizations to provide replication weights as part of survey data files. These replication weights are meant to produce valid and efficient variance estimates for a variety of estimators in a simple and systematic manner. Most existing methods for constructing replication weights, however, are only valid for specific sampling designs and typically require a very large number of replicates. In this paper we first show how to produce replication weights based on the method outlined in Fay (1984) such that the resulting replication variance estimator is algebraically equivalent to the fully efficient linearization variance estimator for any given sampling design. We then propose a novel weight-calibration method to simultaneously achieve efficiency and sparsity in the sense that a small number of sets of replication weights can produce valid and efficient replication variance estimators for key population parameters. Our proposed method can be used in conjunction with existing resampling techniques for large-scale complex surveys. Validity of the proposed methods and extensions to some balanced sampling designs are also discussed. Simulation results showed that our proposed variance estimators perform very well in tracking coverage probabilities of confidence intervals. Our proposed strategies will likely have impact on how public-use survey data files are produced and how these data sets are analyzed.

    Release date: 2013-06-28

  • Articles and reports: 12-001-X201300111828
    Description:

    A question that commonly arises in longitudinal surveys is the issue of how to combine differing cohorts of the survey. In this paper we present a novel method for combining different cohorts, and using all available data, in a longitudinal survey to estimate parameters of a semiparametric model, which relates the response variable to a set of covariates. The procedure builds upon the Weighted Generalized Estimation Equation method for handling missing waves in longitudinal studies. Our method is set up under a joint-randomization framework for estimation of model parameters, which takes into account the superpopulation model as well as the survey design randomization. We also propose a design-based, and a joint-randomization, variance estimation method. To illustrate the methodology we apply it to the Survey of Doctorate Recipients, conducted by the U.S. National Science Foundation.

    Release date: 2013-06-28

  • Articles and reports: 12-001-X201300111829
    Description:

    Indirect Sampling is used when the sampling frame is not the same as the target population, but related to the latter. The estimation process for Indirect Sampling is carried out using the Generalised Weight Share Method (GWSM), which is an unbiased procedure (see Lavallée 2002, 2007). For business surveys, Indirect Sampling is applied as follows: the sampling frame is one of establishments, while the target population is one of enterprises. Enterprises are selected through their establishments. This allows stratifying according to the establishment characteristics, rather than those associated with enterprises. Because the variables of interest of establishments are generally highly skewed (a small portion of the establishments covers the major portion of the economy), the GWSM results in unbiased estimates, but their variance can be large. The purpose of this paper is to suggest some adjustments to the weights to reduce the variance of the estimates in the context of skewed populations, while keeping the method unbiased. After a brief overview of Indirect Sampling and the GWSM, we describe the required adjustments to the GWSM. The estimates produced with these adjustments are compared to those from the original GWSM, via a small numerical example, and using real data originating from the Statistics Canada's Business Register.

    Release date: 2013-06-28

  • Articles and reports: 12-001-X201300111830
    Description:

    We consider two different self-benchmarking methods for the estimation of small area means based on the Fay-Herriot (FH) area level model: the method of You and Rao (2002) applied to the FH model and the method of Wang, Fuller and Qu (2008) based on augmented models. We derive an estimator of the mean squared prediction error (MSPE) of the You-Rao (YR) estimator of a small area mean that, under the true model, is correct to second-order terms. We report the results of a simulation study on the relative bias of the MSPE estimator of the YR estimator and the MSPE estimator of the Wang, Fuller and Qu (WFQ) estimator obtained under an augmented model. We also study the MSPE and the estimators of MSPE for the YR and WFQ estimators obtained under a misspecified model.

    Release date: 2013-06-28

  • Articles and reports: 12-001-X201300111831
    Description:

    We consider conservative variance estimation for the Horvitz-Thompson estimator of a population total in sampling designs with zero pairwise inclusion probabilities, known as "non-measurable" designs. We decompose the standard Horvitz-Thompson variance estimator under such designs and characterize the bias precisely. We develop a bias correction that is guaranteed to be weakly conservative (nonnegatively biased) regardless of the nature of the non-measurability. The analysis sheds light on conditions under which the standard Horvitz-Thompson variance estimator performs well despite non-measurability and where the conservative bias correction may outperform commonly-used approximations.

    Release date: 2013-06-28

  • 40. Survey Quality Archived
    Articles and reports: 12-001-X201200211751
    Description:

    Survey quality is a multi-faceted concept that originates from two different development paths. One path is the total survey error paradigm that rests on four pillars providing principles that guide survey design, survey implementation, survey evaluation, and survey data analysis. We should design surveys so that the mean squared error of an estimate is minimized given budget and other constraints. It is important to take all known error sources into account, to monitor major error sources during implementation, to periodically evaluate major error sources and combinations of these sources after the survey is completed, and to study the effects of errors on the survey analysis. In this context survey quality can be measured by the mean squared error and controlled by observations made during implementation and improved by evaluation studies. The paradigm has both strengths and weaknesses. One strength is that research can be defined by error sources and one weakness is that most total survey error assessments are incomplete in the sense that it is not possible to include the effects of all the error sources. The second path is influenced by ideas from the quality management sciences. These sciences concern business excellence in providing products and services with a focus on customers and competition from other providers. These ideas have had a great influence on many statistical organizations. One effect is the acceptance among data providers that product quality cannot be achieved without a sufficient underlying process quality and process quality cannot be achieved without a good organizational quality. These levels can be controlled and evaluated by service level agreements, customer surveys, paradata analysis using statistical process control, and organizational assessment using business excellence models or other sets of criteria. All levels can be improved by conducting improvement projects chosen by means of priority functions. The ultimate goal of improvement projects is that the processes involved should gradually approach a state where they are error-free. Of course, this might be an unattainable goal, albeit one to strive for. It is not realistic to hope for continuous measurements of the total survey error using the mean squared error. Instead one can hope that continuous quality improvement using management science ideas and statistical methods can minimize biases and other survey process problems so that the variance becomes an approximation of the mean squared error. If that can be achieved we have made the two development paths approximately coincide.

    Release date: 2012-12-19
Reference (23)

Reference (23) (0 to 10 of 23 results)

  • Surveys and statistical programs – Documentation: 84-538-X
    Geography: Canada
    Description: This electronic publication presents the methodology underlying the production of the life tables for Canada, provinces and territories.
    Release date: 2023-08-28

  • Surveys and statistical programs – Documentation: 32-26-0006
    Description: This report provides data quality information pertaining to the Agriculture–Population Linkage, such as sources of error, matching process, response rates, imputation rates, sampling, weighting, disclosure control methods and data quality indicators.
    Release date: 2023-08-25

  • Classification: 12-590-X
    Description:

    The Classification of Instructional Programs (CIP) is used for classifying instructional programs according to field of study. CIP was originally created by the National Center for Education Statistics (NCES) in the United States. It is a hierarchical classification. The classification provides a detailed description of each instructional program class together with illustrative examples of the types of instructional programs found in that class. Illustrative examples are also provided of closely related programs that are classified elsewhere. In addition, the classification includes an introduction to CIP and an alternative structure for the aggregation of field of study data. CIP has a ten-year revision cycle.

    Release date: 2022-11-08

  • Notices and consultations: 98-26-0001
    Description:

    This white paper presents Statistics Canada’s planned approach to the 2021 Census of Population and provides a clear explanation of the processes behind the census program, touching on historical, legal, operational and content aspects. Statistics Canada recognizes that it is important to not only successfully conduct the census, but also to be transparent and informative about the way in which those efforts are accomplished. Painting a Portrait of Canada: The 2021 Census of Population gives readers an exclusive, detailed look at how census data is collected, analyzed and given back to Canadians, in the form of high-quality statistical information, used to make evidence-based decisions in Canadian society.

    Release date: 2020-07-20

  • Surveys and statistical programs – Documentation: 11-633-X2019001
    Description:

    The mandate of the Analytical Studies Branch (ASB) is to provide high-quality, relevant and timely information on economic, health and social issues that are important to Canadians. The branch strategically makes use of expert knowledge and a large range of statistical sources to describe, draw inferences from, and make objective and scientifically supported deductions about the evolving nature of the Canadian economy and society. Research questions are addressed by applying leading-edge methods, including microsimulation and predictive analytics using a range of linked and integrated administrative and survey data. In supporting greater access to data, ASB linked data are made available to external researchers and policy makers to support evidence-based decision making. Research results are disseminated by the branch using a range of mediums (i.e., research papers, studies, infographics, videos, and blogs) to meet user needs. The branch also provides analytical support and training, feedback, and quality assurance to the wide range of programs within and outside Statistics Canada.

    Release date: 2019-05-29

  • Notices and consultations: 12-002-X
    Description:

    The Research Data Centres (RDCs) Information and Technical Bulletin (ITB) is a forum by which Statistics Canada analysts and the research community can inform each other on survey data uses and methodological techniques. Articles in the ITB focus on data analysis and modelling, data management, and best or ineffective statistical, computational, and scientific practices. Further, ITB topics will include essays on data content, implications of questionnaire wording, comparisons of datasets, reviews on methodologies and their application, data peculiarities, problematic data and solutions, and explanations of innovative tools using RDC surveys and relevant software. All of these essays may provide advice and detailed examples outlining commands, habits, tricks and strategies used to make problem-solving easier for the RDC user.

    The main aims of the ITB are:

    - the advancement and dissemination of knowledge surrounding Statistics Canada's data; - the exchange of ideas among the RDC-user community;- the support of new users; - the co-operation with subject matter experts and divisions within Statistics Canada.

    The ITB is interested in quality articles that are worth publicizing throughout the research community, and that will add value to the quality of research produced at Statistics Canada's RDCs.

    Release date: 2015-03-25

  • Surveys and statistical programs – Documentation: 91-549-X
    Geography: Canada
    Description:

    The main objective of this document is to raise awareness among Statistics Canada data users of the different sources of language data available at Statistics Canada. Along with the census, surveys with an important sample of official-language minority groups and/or with information on languages are listed by themes. Users will find a description of the survey and its target population, sample sizes (total and according to available linguistic characteristics), available language variables based on questions asked, date of the first release, year for which the data is available and a direct internet link to additional information on the various surveys.

    Release date: 2013-05-29

  • Surveys and statistical programs – Documentation: 12-593-X
    Description: A guide for elementary and secondary teachers on the basic skills involved in statistical investigation: choosing the dataset, understanding data concepts and analysing the data with or without computer software.
    Release date: 2010-09-24

  • Surveys and statistical programs – Documentation: 92-569-X2006002
    Description:

    The 2006 Census Technical Report on Aboriginal Peoples deals with: (i) Aboriginal ancestry, (ii) Aboriginal identity, (iii) registered Indian status, and (iv) First Nation or Band membership. The report aims to inform users about the complexity of the data and any difficulties that could affect their use. It explains the conceptual framework and definitions used to gather the data, and it discusses factors that could affect data quality. The historical comparability of the data is also discussed.

    The second edition includes the same content as the first, and new text has been added on data processing (Chapter 3). As well, modified content about data quality and 'on reserve' communities has been incorporated into the original sections.

    Release date: 2010-02-09

  • Surveys and statistical programs – Documentation: 92-569-X
    Description:

    The 2006 Census Technical Report on Aboriginal Peoples deals with: (i) Aboriginal ancestry, (ii) Aboriginal identity, (iii) registered Indian status, and (iv) First Nation or Band membership. The report aims to inform users about the complexity of the data and any difficulties that could affect their use. It explains the conceptual framework and definitions used to gather the data, and it discusses factors that could affect data quality. The historical comparability of the data is also discussed.

    Release date: 2010-02-09
Date modified: