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All (66)
All (66) (50 to 60 of 66 results)
- Articles and reports: 12-001-X20000025539Description:
In this paper we will combine two applications of multilevel models. The multilevel model is suitable to analyze interviewer effects on survey data. It can also be used to analyze longitudinal - "repeated measurements" - data. We will analyze a data quality indicator of panel data that come from the Belgian Election Studies.
Release date: 2001-02-28 - Articles and reports: 15-204-X19990005495Description:
This chapter examines productivity growth in manufacturing by size of establishment and by whether it is Canadian- or foreign-owned.
Release date: 2001-02-14 - Notices and consultations: 63F0022XDescription:
Statistics Canada's annual retail trade surveys are undergoing changes. Two activities underlie these changes. The re-design of our annual retail trade questionnaires is one. The other is the conversion from the 1980 Standard Industrial Classification (1980 SIC) to the North American Industrial Classification System (NAICS). These activities will have significant impacts on the output of the annual surveys.
This paper has two goals. The first is to inform retail store data users, industry analysts, trade associations and other stakeholders about these changes. The second is to consult with stakeholders on possible data outputs resulting from the changes.
The paper is organized into five parts. Following the introduction, Part II describes the outputs from the current surveys and compares and contrasts the current outputs with the new. Part III focuses on the introduction of NAICS codes and the changes in coverage for retail trade. In Part IV, the benefits resulting from the above changes are outlined. The final part (Part V) seeks comments or suggestions from data users, retail trade associations and industry specialists on the release of data products as a result of the changes to the surveys.
Release date: 2001-02-01 - 54. Census Metropolitan Area and Census Agglomeration Influenced Zones (MIZ) with Census Data ArchivedTable: 92F0138M2000001Description:
With this working paper, Statistics Canada is releasing 1991 Census data tabulated by a new geographic classification called "census metropolitan area and census agglomeration influenced zones", or MIZ. This classification applies to census subdivisions (municipalities) that lie outside census metropolitan areas and census agglomerations. This part of Canada covers 96% of the country's total land mass and contains 22% of its population, yet up to now we have been limited in our means of differentiating this vast area. The MIZ classification shows the influence of census metropolitan areas (CMA) and census agglomerations (CA) on surrounding census subdivisions as measured by commuting flows based on 1991 Census place of work data. This version of the MIZ classification also incorporates a preliminary version of a north concept that flags census subdivisions according to their location in the north or south of Canada.
The series of tables presented here show detailed demographic, social and economic characteristics for Canada as a whole, for the six major regions of Canada, and for individual provinces and territories. Within each table, the data are subdivided into five categories: census metropolitan area or census agglomeration, strong MIZ, moderate MIZ, weak MIZ and no MIZ. Within each of these categories, the data are further subdivided into north and south.
Readers are invited to review and use the data tables to assess whether this combined MIZ and north/south classification of non-CMA/CA areas provides sufficient detail to support data analysis and research. The intent of this MIZ classification is to reveal previously hidden data detail and thereby help users address issues related to this vast geographic area.
This is the first of three related Geography working papers (catalogue no. 92F0138MPE). The second working paper (no. 2000-2, 92F0138MPE00002) provides background information about the methodology used to delineate the MIZ classification. The third working paper (no. 2000-3, 92F0138MPE00003) describes the methodology used to define a continuous line across Canada that separates the north from the south to further differentiate the MIZ classification.
Release date: 2000-02-03 - 55. Census Metropolitan Area and Census Agglomeration Influenced Zones (MIZ): A Description of the Methodology ArchivedArticles and reports: 92F0138M2000002Description:
This working paper provides an overview of census metropolitan and census agglomeration influenced zones, or MIZ, their background and the methodology used to define them. The MIZ classification is an approach to better differentiate areas of Canada outside of census metropolitan areas (CMA) and census agglomerations (CA). Census subdivisions that lie outside these areas are classified into one of four zones of influence ranging from "strong" to "no" influence according to the degree of influence that CMA/CAs have on them. The MIZ classification fills a gap in Statistics Canada's geographic framework and promotes data integration since we expect it will be possible to obtain survey data as well as census data based on the same geographic structure. Studies done with a preliminary version of MIZ showed the potential of MIZ to reveal the diversity of non-metropolitan Canada. Based on feedback received on that initial research, this working paper reports on more recent work that has been done to refine the number and data breakpoints for MIZ categories and to examine the additional variables of distances between census subdivisions (CSDs), physical adjacency and a north-south allocation.
This is the second in a series of three related Geography working papers (catalogue no. 92F0138MPE) that describe a new statistical area classification that includes census metropolitan areas/census agglomerations, MIZ and the North concept. The first working paper (no. 2000-1, 92F0138MPE00001) briefly describes MIZ and provides tables of selected socio-economic characteristics from the 1991 Census tabulated by the MIZ categories. The third working paper (no. 2000-3, 92F0138MPE00003) describes the North concept and the methodology used to define a continuous line across Canada that separates the north from the south to further differentiate the MIZ classification.
Release date: 2000-02-03 - 56. Delineation of Canada's North: An Examination of the North-South Relationship in Canada ArchivedArticles and reports: 92F0138M2000003Description:
Statistics Canada's interest in a common delineation of the north for statistical analysis purposes evolved from research to devise a classification to further differentiate the largely rural and remote areas that make up 96% of Canada's land area. That research led to the establishment of the census metropolitan area and census agglomeration influenced zone (MIZ) concept. When applied to census subdivisions, the MIZ categories did not work as well in northern areas as in the south. Therefore, the Geography Division set out to determine a north-south divide that would differentiate the north from the south independent of any standard geographic area boundaries.
This working paper describes the methodology used to define a continuous line across Canada to separate the north from the south, as well as lines marking transition zones on both sides of the north-south line. It also describes the indicators selected to derive the north-south line and makes comparisons to alternative definitions of the north. The resulting classification of the north complements the MIZ classification. Together, census metropolitan areas, census agglomerations, MIZ and the North form a new Statistical Area Classification (SAC) for Canada.
Two related Geography working papers (catalogue no. 92F0138MPE) provide further details about the MIZ classification. Working paper no. 2000-1 (92F0138MPE00001) briefly describes MIZ and includes tables of selected socio-economic characteristics from the 1991 Census tabulated by the MIZ categories, and working paper no. 2000-2 (92F0138MPE00002) describes the methodology used to define the MIZ classification.
Release date: 2000-02-03 - Surveys and statistical programs – Documentation: 92-370-XDescription:
Series description
This series includes five general reference products - the Preview of Products and Services; the Catalogue; the Dictionary; the Handbook and the Technical Reports - as well as geography reference products - GeoSuite and Reference Maps.
Product description
Technical Reports examine the quality of data from the 1996 Census, a large and complex undertaking. While considerable effort was taken to ensure high quality standards throughout each step, the results are subject to a certain degree of error. Each report looks at the collection and processing operations and presents results from data evaluation, as well as notes on historical comparability.
Technical Reports are aimed at moderate and sophisticated users but are written in a manner which could make them useful to all census data users. Most of the technical reports have been cancelled, with the exception of Age, Sex, Marital Status and Common-law Status, Coverage and Sampling and Weighting. These reports will be available as bilingual publications as well as being available in both official languages on the Internet as free products.
This report deals with coverage errors, which occured when persons, households, dwellings or families were missed by the 1996 Census or enumerated in error. Coverage errors are one of the most important types of error since they affect not only the accuracy of the counts of the various census universes but also the accuracy of all of the census data describing the characteristics of these universes. With this information, users can determine the risks involved in basing conclusions or decisions on census data.
Release date: 1999-12-14 - Surveys and statistical programs – Documentation: 11-522-X19980015022Description:
This article extends and further develops the method proposed by Pfeffermann, Skinner and Humphreys (1998) for the estimation of gross flows in the presence of classification errors. The main feature of that method is the use of auxiliary information at the individual level which circumvents the need for validation data for estimating the misclassification rates. The new developments in this article are the establishment of conditions for model identification, a study of the properties of a model goodness of fit statistic and modifications to the sample likelihood to account for missing data and informative sampling. The new developments are illustrated by a small Monte-Carlo simulation study.
Release date: 1999-10-22 - Articles and reports: 63-016-X19990014622Geography: CanadaDescription:
The North American Industrial Classification System (NAICS) is being adopted by Statistics Canada to replace the 1980 Standard Industrial Classification (SIC) system used during the past two decades. The impetus behind NAICS was the North American Free Trade Agreement (NAFTA) and the resultant need for the three signatories (Canada, the United States and Mexico) to have a statistical framework enabling industrial statistics to be collected, analyzed and disseminated in a consistent manner by all three countries on an industry-by-industry basis.
Release date: 1999-07-15 - 60. North American Industry Classification System ArchivedSurveys and statistical programs – Documentation: 53-222-X19970004367Description:
This study deals with the introduction of the newly developed North American Industry Classification system (NAICS), and its impact on the Trucking surveys at Statistics Canada. This paper provides an overview of the uses and needs of an industry classification system and the processes involved in the collection, implementation and dissemination of trucking statistics based on this new classification.
Release date: 1999-02-09
Data (7)
Data (7) ((7 results))
- Table: 99-012-X2011057Geography: Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration partDescription:
This table presents a cross-tabulation of data using selected characteristics from the National Household Survey.
Release date: 2013-12-11 - Table: 99-012-X2011058Geography: Province or territoryDescription:
This table presents a cross-tabulation of data using selected characteristics from the National Household Survey.
Release date: 2013-12-11 - 3. Statistical Area Classification, 2011 ArchivedThematic map: 98-320-X2011003Description:
This map shows the Statistical Area Classification - Variant of SGC 2011. This map illustrates the spatial distribution of CSDs among CMAs, CAs and MIZs.
Release date: 2012-02-08 - Profile of a community or region: 94-581-X2006011Description:
This table contains information from the 2006 Census, presented according to the statistical area classification (SAC). The SAC groups census subdivisions according to whether they are a component of a census metropolitan area, a census agglomeration, a census metropolitan area and census agglomeration influenced zone (strong MIZ, moderate MIZ, weak MIZ or no MIZ) or of the territories (Northwest Territories, Nunavut and Yukon Territory). The SAC is used for data dissemination purposes.
Data characteristics presented according to the SAC include age, marital status, Aboriginal identity, mother tongue, knowledge of official languages, mobility status, immigration, visible minority groups, education, labour force activity, occupation, industry, income and dwellings. Data are presented for Canada, provinces and territories. The data characteristics presented within this table may differ from those of other products in the "Profiles" series.
Release date: 2008-11-25 - Table: 97-556-X2006021Description:
Data for Canada, provinces, territories and census metropolitan areas are shown in this table.
This table is part of the topic 'Mobility and migration', which presents data on the geographic mobility of Canadians; that is, on place of residence one year and five years prior to the census. These data include changes in place of residence for persons who moved within Canada and place of origin for persons who moved to Canada from another country at a given point in time.
It is possible to subscribe to all the day-of-release topic bundles. Refer to Catalogue no. 97-569-XCB for more information.
Release date: 2008-04-08 - Profile of a community or region: 95F0495X2001012Description:
This table contains information from the 2001 Census, presented according to the statistical area classification (SAC). The SAC groups census subdivisions according to whether they are a component of a census metropolitan area, a census agglomeration, a census metropolitan area and census agglomeration influenced zone (strong MIZ, moderate MIZ, weak MIZ or no MIZ) or of the territories (Northwest Territories, Nunavut and Yukon Territory). The SAC is used for data dissemination purposes.
Data characteristics presented according to the SAC include age, visible minority groups, immigration, mother tongue, education, income, work and dwellings. Data are presented for Canada, provinces and territories. The data characteristics presented within this table may differ from those of other products in the "Profiles" series.
Release date: 2004-02-27 - 7. Census Metropolitan Area and Census Agglomeration Influenced Zones (MIZ) with Census Data ArchivedTable: 92F0138M2000001Description:
With this working paper, Statistics Canada is releasing 1991 Census data tabulated by a new geographic classification called "census metropolitan area and census agglomeration influenced zones", or MIZ. This classification applies to census subdivisions (municipalities) that lie outside census metropolitan areas and census agglomerations. This part of Canada covers 96% of the country's total land mass and contains 22% of its population, yet up to now we have been limited in our means of differentiating this vast area. The MIZ classification shows the influence of census metropolitan areas (CMA) and census agglomerations (CA) on surrounding census subdivisions as measured by commuting flows based on 1991 Census place of work data. This version of the MIZ classification also incorporates a preliminary version of a north concept that flags census subdivisions according to their location in the north or south of Canada.
The series of tables presented here show detailed demographic, social and economic characteristics for Canada as a whole, for the six major regions of Canada, and for individual provinces and territories. Within each table, the data are subdivided into five categories: census metropolitan area or census agglomeration, strong MIZ, moderate MIZ, weak MIZ and no MIZ. Within each of these categories, the data are further subdivided into north and south.
Readers are invited to review and use the data tables to assess whether this combined MIZ and north/south classification of non-CMA/CA areas provides sufficient detail to support data analysis and research. The intent of this MIZ classification is to reveal previously hidden data detail and thereby help users address issues related to this vast geographic area.
This is the first of three related Geography working papers (catalogue no. 92F0138MPE). The second working paper (no. 2000-2, 92F0138MPE00002) provides background information about the methodology used to delineate the MIZ classification. The third working paper (no. 2000-3, 92F0138MPE00003) describes the methodology used to define a continuous line across Canada that separates the north from the south to further differentiate the MIZ classification.
Release date: 2000-02-03
Analysis (22)
Analysis (22) (0 to 10 of 22 results)
- Articles and reports: 11-522-X202100100012Description: The modernization of price statistics by National Statistical Offices (NSO) such as Statistics Canada focuses on the adoption of alternative data sources that include the near-universe of all products sold in the country, a scale that requires machine learning classification of the data. The process of evaluating classifiers to select appropriate ones for production, as well as monitoring classifiers once in production, needs to be based on robust metrics to measure misclassification. As commonly utilized metrics, such as the Fß-score may not take into account key aspects applicable to prices statistics in all cases, such as unequal importance of categories, a careful consideration of the metric space is necessary to select appropriate methods to evaluate classifiers. This working paper provides insight on the metric space applicable to price statistics and proposes an operational framework to evaluate and monitor classifiers, focusing specifically on the needs of the Canadian Consumer Prices Index and demonstrating discussed metrics using a publicly available dataset.
Key Words: Consumer price index; supervised classification; evaluation metrics; taxonomy
Release date: 2021-11-05 - Articles and reports: 11-522-X202100100013Description: Statistics Canada’s Labour Force Survey (LFS) plays a fundamental role in the mandate of Statistics Canada. The labour market information provided by the LFS is among the most timely and important measures of the Canadian economy’s overall performance. An integral part of the LFS monthly data processing is the coding of respondent’s industry according to the North American Industrial Classification System (NAICS), occupation according to the National Occupational Classification System (NOC) and the Primary Class of Workers (PCOW). Each month, up to 20,000 records are coded manually. In 2020, Statistics Canada worked on developing Machine Learning models using fastText to code responses to the LFS questionnaire according to the three classifications mentioned previously. This article will provide an overview on the methodology developed and results obtained from a potential application of the use of fastText into the LFS coding process.
Key Words: Machine Learning; Labour Force Survey; Text classification; fastText.
Release date: 2021-11-05 - Articles and reports: 11-522-X202100100003Description:
The increasing size and richness of digital data allow for modeling more complex relationships and interactions, which is the strongpoint of machine learning. Here we applied gradient boosting to the Dutch system of social statistical datasets to estimate transition probabilities into and out of poverty. Individual estimates are reasonable, but the main advantages of the approach in combination with SHAP and global surrogate models are the simultaneous ranking of hundreds of features by their importance, detailed insight into their relationship with the transition probabilities, and the data-driven identification of subpopulations with relatively high and low transition probabilities. In addition, we decompose the difference in feature importance between general and subpopulation into a frequency and a feature effect. We caution for misinterpretation and discuss future directions.
Key Words: Classification; Explainability; Gradient boosting; Life event; Risk factors; SHAP decomposition.
Release date: 2021-10-15 - Journals and periodicals: 57-602-GDescription:
The objective of this document is to present a proposed Statistical Framework for Energy in Canada, which will help guide data providers and users in the development of a strategic plan for addressing priority elements of the proposed framework.
The framework is intended to apply to energy statistics in Canada in general, with application across a broad range of stakeholders involved in the collection, dissemination and use of energy statistics, including provincial and territorial administrative and statistical agencies.
Release date: 2016-02-19 - Articles and reports: 13-605-X201501014292Description:
This article describes the revisions to the balance of payments data and related statistical products introduced as part of the 2015 Comprehensive Revision of the Canadian System of Macroeconomic Accounts (CSMA). This exercise is conducted to strengthen the overall quality of the international accounts program and to introduce new concepts and classifications as recommended by updated international standards. The revisions are also harmonized with those of the corresponding accounts in the CSMA.
Release date: 2015-11-30 - Articles and reports: 12-001-X201200111683Description:
We consider alternatives to poststratification for doubly classified data in which at least one of the two-way cells is too small to allow the poststratification based upon this double classification. In our study data set, the expected count in the smallest cell is 0.36. One approach is simply to collapse cells. This is likely, however, to destroy the double classification structure. Our alternative approaches allows one to maintain the original double classification of the data. The approaches are based upon the calibration study by Chang and Kott (2008). We choose weight adjustments dependent upon the marginal classifications (but not full cross classification) to minimize an objective function of the differences between the population counts of the two way cells and their sample estimates. In the terminology of Chang and Kott (2008), if the row and column classifications have I and J cells respectively, this results in IJ benchmark variables and I + J - 1 model variables. We study the performance of these estimators by constructing simulation simple random samples from the 2005 Quarterly Census of Employment and Wages which is maintained by the Bureau of Labor Statistics. We use the double classification of state and industry group. In our study, the calibration approaches introduced an asymptotically trivial bias, but reduced the MSE, compared to the unbiased estimator, by as much as 20% for a small sample.
Release date: 2012-06-27 - 7. Self-contained Labour Areas: A Proposed Delineation and Classification by Degree of Rurality ArchivedArticles and reports: 21-006-X2008008Geography: CanadaDescription:
One of the most common terms in economic and social reporting is that of "labour market". This concept is normally used with two main connotations, which to some extent overlap. The first emphasizes a set of employment norms, practices and trends that are in some cases specific to certain occupations or industries. The second connotation emphasizes the spatial dimension of the market, as the geographic area in which a multitude of labour activities occur. In this bulletin, our focus is on this second aspect: we identify a set of self-contained labour areas (SLAs), which in broad terms can be described as geographic spaces in which the majority of the residents in the labour force also have their place of work.
Release date: 2011-12-19 - Articles and reports: 82-003-X200800410747Geography: CanadaDescription:
A selective approach may be used in an ecological study where the aim is to choose a subset of units of analysis (UAs) and produce interpretations about a population of interest (PI) based solely on those UAs. The results for the PI will be reliable if that population is concentrated in the selected UAs and rare in other UAs. This article presents a graphical tool that helps determine whether these conditions are satisfied.
Release date: 2008-12-17 - 9. Labour Force Classification in SLID ArchivedArticles and reports: 75F0002M1992006Description:
Labour force status will be an important analytical variable for many users of SLID data. The document discusses the issues involved in deriving this variable, and details the approach to be adopted.
Briefly, a value will be assigned for every one-week period, with three possibilities: employed, unemployed and not in the labour force. To a large extent, concepts used in the Canadian Labour Force Survey will be used. Since there are several situations where a straightforward approach to the classification is not possible, additional information will be available to data users who wish to adjust the definitions used.
Release date: 2008-02-29 - Articles and reports: 12-001-X200700210492Description:
Multiple Frame Surveys were originally proposed to foster cost savings on the basis of an optimality approach. As surveys on special, rare and difficult-to-sample populations are becoming more prominent, a single list of population units to be used as a sampling frame is often unavailable in sampling practice. In recent literature multiple frame designs have been put forward in order to increase population coverage, to improve response rates and to capture differences and subgroups. Alternative approaches to multiple frame estimation have appeared, all of them relying upon the virtual partition of the set of the available overlapping frames into disjointed domains. Hence the correct classification of sampled units into the domains is required for practical applications. In this paper a multiple frame estimator is proposed using a multiplicity approach. Multiplicity estimators require less information about unit domain membership hence they are insensitive to misclassification. Moreover the proposed estimator is analytically simple so that it is easy to implement and its exact variance is given. Empirical results from an extensive simulation study comparing the multiplicity estimator with major competitors are also provided.
Release date: 2008-01-03
Reference (37)
Reference (37) (0 to 10 of 37 results)
- Classification: 65-209-XDescription: The Canadian Export Classification is a structured, hierarchical classification system based on the Harmonized Description and Coding System. The HS nomenclature is divided into 21 Sections, which in general, group goods produced in the same sector of the economy.Release date: 2023-12-06
- Classification: 12-590-XDescription:
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 - Geographic files and documentation: 12-571-XDescription:
The Standard Geographical Classification (SGC) provides a systematic classification structure that categorizes all of the geographic area of Canada. The SGC is the official classification used in the Census of Population and other Statistics Canada surveys.
The classification is organized in two volumes: Volume I, The Classification and Volume II, Reference Maps.
Volume I describes the classification and related standard geographic areas and place names. It provides names and codes for the geographical regions of Canada, provinces and territories, census divisions (counties, regional municipalities) and census subdivisions (municipalities). The names and codes for census metropolitan areas, census agglomerations, census metropolitan influenced zones, economic regions, census agricultural regions and census consolidated subdivisions are shown in the classification variants of the SGC. Volume I explains the changes between the current version of the SGC and the previous version that impact upon the classification, such as changes in name, type or code, and indicates how the new and old codes relate to one another.
Reference maps showing the locations and boundaries of the standard geographic areas in the classification are in Volume II, Reference Maps
Release date: 2022-02-09 - Classification: 12-501-XDescription:
The North American Industry Classification System (NAICS) is an industry classification system developed by the statistical agencies of Canada, Mexico and the United States. Created against the background of the North American Free Trade Agreement, it is designed to provide common definitions of the industrial structure of the three countries and a common statistical framework to facilitate the analysis of the three economies. NAICS is based on supply-side or production-oriented principles, to ensure that industrial data, classified to NAICS, are suitable for the analysis of production-related issues such as industrial performance.
NAICS is a comprehensive system encompassing all economic activities. It has a hierarchical structure. At the highest level, it divides the economy into 20 sectors. At lower levels, it further distinguishes the different economic activities in which businesses are engaged.
Email: statcan.csds-standards-industry-cnsd-normes-industrie.statcan@statcan.gc.ca
Release date: 2022-01-27 - Classification: 12-583-XDescription:
This publication provides a systematic classification structure to identify and categorize the entire range of occupational activity in Canada. Definitions and occupational titles are provided for each unit group. An alphabetical index of the occupational titles classified to the unit group level is also included.
Release date: 2021-09-21 - Classification: 89-26-0004Description: This classification system was developed conjointly by the Social Sciences and Humanities Research Council of Canada (SSHRC), the Natural Sciences and Engineering Research Council of Canada (NSERC), the Canada Foundation for Innovation (CFI), the Canadian Institutes of Health Research (CIHR), and Statistics Canada which is the custodian. This shared standard classification, inspired by the Frascati Model 2015 of the Organisation for Economic Co-operation and Development (OECD), will be used by the federal granting agencies and Statistics Canada to collect and disseminate data related to research and development in Canada. The Canadian Research and Development Classification (CRDC) first official version is the 2020 version 1.0. The CRDC will be revised within 2 years of its first release and on a five-year cycle after that, with possibility of 'evergreening' for minor changes once a year to reflect the changes in the research fields. CRDC 2020 version 1.0 is composed of 3 main pieces: the type of activity or TOA (with 3 categories), the field of research or FOR (with 1663 fields at the lowest level) and socioeconomic objective or SEO (with 85 main groups at the lowest level).Release date: 2020-10-05
- Surveys and statistical programs – Documentation: 12-539-XDescription:
This document brings together guidelines and checklists on many issues that need to be considered in the pursuit of quality objectives in the execution of statistical activities. Its focus is on how to assure quality through effective and appropriate design or redesign of a statistical project or program from inception through to data evaluation, dissemination and documentation. These guidelines draw on the collective knowledge and experience of many Statistics Canada employees. It is expected that Quality Guidelines will be useful to staff engaged in the planning and design of surveys and other statistical projects, as well as to those who evaluate and analyze the outputs of these projects.
Release date: 2019-12-04 - Surveys and statistical programs – Documentation: 11-621-M2018105Description:
Statistics Canada needs to respond to the legalization of cannabis for non-medical use by measuring various aspects of the introduction of cannabis in the Canadian economy and society. An important part of measuring the economy and society is using statistical classifications. It is common practice with classifications that they are updated and revised as new industries, products, occupations and educational programs are introduced into the Canadian economy and society. This paper describes the changes to the various statistical classifications used by Statistics Canada in order to measure the introduction of legal non-medical cannabis.
Release date: 2019-07-24 - Surveys and statistical programs – Documentation: 13-606-G201600114618Description:
An explanation of key national accounting concepts involving stocks and flows; the distinction between price and volume changes; production, distribution, consumption and accumulation; residence; institutional units and sectors; classifications; and accounting concepts. Also includes a description of SNA 2008’s sequence of accounts.
Release date: 2016-05-31 - Surveys and statistical programs – Documentation: 99-012-X2011006Geography: CanadaDescription:
This reference guide provides information that enables users to effectively use, apply and interpret data from the 2011 National Household Survey (NHS). This guide contains definitions and explanations of concepts, classifications, data quality and comparability to other sources. Additional information is included for specific variables to help general users better understand the concepts and questions used in the NHS.
Release date: 2013-06-26
- Date modified: