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All (62) (0 to 10 of 62 results)

  • Stats in brief: 45-28-0001202100100040
    Description:

    This article analyzes the Canada Emergency Wage Subsidy Regional and Community-level Database from a rural business perspective. This database covers the period from October 25, 2020 to January 16, 2021. It is based on Canada Revenue Agency (CRA) Canada Emergency Wage Subsidy (CEWS) microdata and administrative data sources available within Statistics Canada. Topics include number of CEWS supported employees and subsidy amounts in rural areas, comparison of rural and urban businesses, and analysis by industry and province/territory.

    Release date: 2021-12-06

  • Stats in brief: 11-627-M2021072
    Description:

    This infographic features indicators on apprenticeship programs across Canada. It presents the year-over-year changes in new registrations and certifications amongst trade groups and jurisdictions in 2020. This infographic will also highlight some of the impacts of COVID-19 on apprenticeship programs.

    Release date: 2021-12-06

  • Articles and reports: 82-003-X202101100002
    Description:

    There are important information gaps concerning the prevalence and distribution of infection control practices within workplaces continuing to operate during the COVID-19 pandemic.

    Release date: 2021-11-17

  • Stats in brief: 45-28-0001202100100037
    Description:

    This article uses data from the Labour Force Survey to examine trends in employment, unemployment and labour force participation among Indigenous people in the 18 months following the onset of the COVID-19 pandemic. Trends for Indigenous and non-Indigenous people, by age group, sex, region and occupation, as well as for First Nations people and Métis, are presented.

    Release date: 2021-11-16

  • Articles and reports: 11-633-X2021007
    Description:

    Statistics Canada continues to use a variety of data sources to provide neighbourhood-level variables across an expanding set of domains, such as sociodemographic characteristics, income, services and amenities, crime, and the environment. Yet, despite these advances, information on the social aspects of neighbourhoods is still unavailable. In this paper, answers to the Canadian Community Health Survey on respondents’ sense of belonging to their local community were pooled over the four survey years from 2016 to 2019. Individual responses were aggregated up to the census tract (CT) level.

    Release date: 2021-11-16

  • Articles and reports: 11-522-X202100100011
    Description: The ways in which AI may affect the world of official statistics are manifold and Statistics Netherlands (CBS) is actively exploring how it can use AI within its societal role. The paper describes a number of AI-related areas where CBS is currently active: use of AI for its own statistics production and statistical R&D, the development of a national AI monitor, the support of other government bodies with expertise on fair data and fair algorithms, data sharing under safe and secure conditions, and engaging in AI-related collaborations.

    Key Words: Artificial Intelligence; Official Statistics; Data Sharing; Fair Algorithms; AI monitoring; Collaboration.

    Release date: 2021-11-05

  • Articles and reports: 81-582-X2021003
    Description: The Pan-Canadian Education Indicators Program (PCEIP) draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, and labour market outcomes. PCEIP products include tables, fact sheets, reports and a methodological handbook. They present indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. The Pan-Canadian Education Indicators Program (PCEIP) is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
    Release date: 2021-11-01

  • Articles and reports: 11-522-X202100100008
    Description:

    Non-probability samples are being increasingly explored by National Statistical Offices as a complement to probability samples. We consider the scenario where the variable of interest and auxiliary variables are observed in both a probability and non-probability sample. Our objective is to use data from the non-probability sample to improve the efficiency of survey-weighted estimates obtained from the probability sample. Recently, Sakshaug, Wisniowski, Ruiz and Blom (2019) and Wisniowski, Sakshaug, Ruiz and Blom (2020) proposed a Bayesian approach to integrating data from both samples for the estimation of model parameters. In their approach, non-probability sample data are used to determine the prior distribution of model parameters, and the posterior distribution is obtained under the assumption that the probability sampling design is ignorable (or not informative). We extend this Bayesian approach to the prediction of finite population parameters under non-ignorable (or informative) sampling by conditioning on appropriate survey-weighted statistics. We illustrate the properties of our predictor through a simulation study.

    Key Words: Bayesian prediction; Gibbs sampling; Non-ignorable sampling; Statistical data integration.

    Release date: 2021-10-29

  • Articles and reports: 11-522-X202100100024
    Description: The Economic Directorate of the U.S. Census Bureau is developing coordinated design and sample selection procedures for the Annual Integrated Economic Survey. The unified sample will replace the directorate’s existing practice of independently developing sampling frames and sampling procedures for a suite of separate annual surveys, which optimizes sample design features at the cost of increased response burden. Size attributes of business populations, e.g., revenues and employment, are highly skewed. A high percentage of companies operate in more than one industry. Therefore, many companies are sampled into multiple surveys compounding the response burden, especially for “medium sized” companies.

    This component of response burden is reduced by selecting a single coordinated sample but will not be completely alleviated. Response burden is a function of several factors, including (1) questionnaire length and complexity, (2) accessibility of data, (3) expected number of repeated measures, and (4) frequency of collection. The sample design can have profound effects on the third and fourth factors. To help inform decisions about the integrated sample design, we use regression trees to identify covariates from the sampling frame that are related to response burden. Using historic frame and response data from four independently sampled surveys, we test a variety of algorithms, then grow regression trees that explain relationships between expected levels of response burden (as measured by response rate) and frame covariates common to more than one survey. We validate initial findings by cross-validation, examining results over time. Finally, we make recommendations on how to incorporate our robust findings into the coordinated sample design.
    Release date: 2021-10-29

  • Articles and reports: 82-625-X202100100004
    Description:

    This document provides descriptive results of the muscle and bone density of the tibia. Descriptive results for lower limb muscle power and force are also presented.

    Release date: 2021-10-27
Stats in brief (22)

Stats in brief (22) (0 to 10 of 22 results)

  • Stats in brief: 45-28-0001202100100040
    Description:

    This article analyzes the Canada Emergency Wage Subsidy Regional and Community-level Database from a rural business perspective. This database covers the period from October 25, 2020 to January 16, 2021. It is based on Canada Revenue Agency (CRA) Canada Emergency Wage Subsidy (CEWS) microdata and administrative data sources available within Statistics Canada. Topics include number of CEWS supported employees and subsidy amounts in rural areas, comparison of rural and urban businesses, and analysis by industry and province/territory.

    Release date: 2021-12-06

  • Stats in brief: 11-627-M2021072
    Description:

    This infographic features indicators on apprenticeship programs across Canada. It presents the year-over-year changes in new registrations and certifications amongst trade groups and jurisdictions in 2020. This infographic will also highlight some of the impacts of COVID-19 on apprenticeship programs.

    Release date: 2021-12-06

  • Stats in brief: 45-28-0001202100100037
    Description:

    This article uses data from the Labour Force Survey to examine trends in employment, unemployment and labour force participation among Indigenous people in the 18 months following the onset of the COVID-19 pandemic. Trends for Indigenous and non-Indigenous people, by age group, sex, region and occupation, as well as for First Nations people and Métis, are presented.

    Release date: 2021-11-16

  • Stats in brief: 45-28-0001202100100038
    Description:

    This article examines some of the effects of COVID-19 on rural businesses in Canada, with comparison to urban counterparts by industry for contextual support. Topics include business obstacles, expectations for the next year, workforce changes and other subjects from the Canadian Survey on Business Conditions, third quarter of 2021.

    Release date: 2021-10-18

  • Stats in brief: 45-28-0001202100100033
    Description:

    The COVID-19 pandemic abruptly disrupted many businesses that create and distribute arts and culture or offer recreational activities. This study looks at preliminary operating revenue estimates and labour-related expenses for the culture, arts, entertainment and recreation sectors in 2020.

    Release date: 2021-08-17

  • Stats in brief: 11-627-M2021061
    Description:

    Key findings about workplace sexual misconduct in the Canadian provinces are presented in this infographic, including statistics on inappropriate sexualized behaviours and discrimination based on sexual orientation and gender identity. Data on workers' attitudes about their workplace and about information that they received from their employer are also presented.

    Release date: 2021-08-12

  • Stats in brief: 45-28-0001202100100028
    Description:

    This article examines some of the effects of COVID-19 on rural businesses in Canada, with comparison to urban counterparts by industry for contextual support. Topics include business obstacles, expectations for the next year, workforce changes and other subjects from the Canadian Survey on Business Conditions, second quarter of 2021.

    Release date: 2021-07-09

  • Stats in brief: 45-28-0001202100100019
    Description:

    The shift by Canadians to a more physically distanced life resulted in a dramatic reduction in the transmission of COVID-19. However, there are concerns that health behaviours, including physical activity, have consequently changed in ways that will result in an unintended increase in the risk of chronic diseases such as cardiovascular disease, obesity, diabetes and cancer. This study looks at how many Canadians could develop cardiovascular disease over the next three years because of reduced levels of physical activity during the COVID-19 pandemic.

    Release date: 2021-06-25

  • Stats in brief: 45-28-0001202100100027
    Description:

    The COVID-19 pandemic has significantly impacted the behaviours of Canadians, particularly regarding their online activities. Using data from the 2020 Canadian Internet Use Survey, this article examines several Internet-related activities Canadians have done more often during the pandemic.

    Release date: 2021-06-24

  • Stats in brief: 11-627-M2021041
    Description:

    This infographic features the pathways of registered apprentices across Canada. It presents the certification, continuation and discontinuation rates of registered apprentices over time as well as key results among 25 selected Red Seal trades, and 5 selected non-Red Seal trades.

    Release date: 2021-06-24
Articles and reports (40)

Articles and reports (40) (0 to 10 of 40 results)

  • Articles and reports: 82-003-X202101100002
    Description:

    There are important information gaps concerning the prevalence and distribution of infection control practices within workplaces continuing to operate during the COVID-19 pandemic.

    Release date: 2021-11-17

  • Articles and reports: 11-633-X2021007
    Description:

    Statistics Canada continues to use a variety of data sources to provide neighbourhood-level variables across an expanding set of domains, such as sociodemographic characteristics, income, services and amenities, crime, and the environment. Yet, despite these advances, information on the social aspects of neighbourhoods is still unavailable. In this paper, answers to the Canadian Community Health Survey on respondents’ sense of belonging to their local community were pooled over the four survey years from 2016 to 2019. Individual responses were aggregated up to the census tract (CT) level.

    Release date: 2021-11-16

  • Articles and reports: 11-522-X202100100011
    Description: The ways in which AI may affect the world of official statistics are manifold and Statistics Netherlands (CBS) is actively exploring how it can use AI within its societal role. The paper describes a number of AI-related areas where CBS is currently active: use of AI for its own statistics production and statistical R&D, the development of a national AI monitor, the support of other government bodies with expertise on fair data and fair algorithms, data sharing under safe and secure conditions, and engaging in AI-related collaborations.

    Key Words: Artificial Intelligence; Official Statistics; Data Sharing; Fair Algorithms; AI monitoring; Collaboration.

    Release date: 2021-11-05

  • Articles and reports: 81-582-X2021003
    Description: The Pan-Canadian Education Indicators Program (PCEIP) draws from a wide variety of data sources to provide information on the school-age population, elementary, secondary and postsecondary education, transitions, and labour market outcomes. PCEIP products include tables, fact sheets, reports and a methodological handbook. They present indicators for all of Canada, the provinces, the territories, as well as selected international comparisons and comparisons over time. The Pan-Canadian Education Indicators Program (PCEIP) is an ongoing initiative of the Canadian Education Statistics Council, a partnership between Statistics Canada and the Council of Ministers of Education, Canada that provides a set of statistical measures on education systems in Canada.
    Release date: 2021-11-01

  • Articles and reports: 11-522-X202100100008
    Description:

    Non-probability samples are being increasingly explored by National Statistical Offices as a complement to probability samples. We consider the scenario where the variable of interest and auxiliary variables are observed in both a probability and non-probability sample. Our objective is to use data from the non-probability sample to improve the efficiency of survey-weighted estimates obtained from the probability sample. Recently, Sakshaug, Wisniowski, Ruiz and Blom (2019) and Wisniowski, Sakshaug, Ruiz and Blom (2020) proposed a Bayesian approach to integrating data from both samples for the estimation of model parameters. In their approach, non-probability sample data are used to determine the prior distribution of model parameters, and the posterior distribution is obtained under the assumption that the probability sampling design is ignorable (or not informative). We extend this Bayesian approach to the prediction of finite population parameters under non-ignorable (or informative) sampling by conditioning on appropriate survey-weighted statistics. We illustrate the properties of our predictor through a simulation study.

    Key Words: Bayesian prediction; Gibbs sampling; Non-ignorable sampling; Statistical data integration.

    Release date: 2021-10-29

  • Articles and reports: 11-522-X202100100024
    Description: The Economic Directorate of the U.S. Census Bureau is developing coordinated design and sample selection procedures for the Annual Integrated Economic Survey. The unified sample will replace the directorate’s existing practice of independently developing sampling frames and sampling procedures for a suite of separate annual surveys, which optimizes sample design features at the cost of increased response burden. Size attributes of business populations, e.g., revenues and employment, are highly skewed. A high percentage of companies operate in more than one industry. Therefore, many companies are sampled into multiple surveys compounding the response burden, especially for “medium sized” companies.

    This component of response burden is reduced by selecting a single coordinated sample but will not be completely alleviated. Response burden is a function of several factors, including (1) questionnaire length and complexity, (2) accessibility of data, (3) expected number of repeated measures, and (4) frequency of collection. The sample design can have profound effects on the third and fourth factors. To help inform decisions about the integrated sample design, we use regression trees to identify covariates from the sampling frame that are related to response burden. Using historic frame and response data from four independently sampled surveys, we test a variety of algorithms, then grow regression trees that explain relationships between expected levels of response burden (as measured by response rate) and frame covariates common to more than one survey. We validate initial findings by cross-validation, examining results over time. Finally, we make recommendations on how to incorporate our robust findings into the coordinated sample design.
    Release date: 2021-10-29

  • Articles and reports: 82-625-X202100100004
    Description:

    This document provides descriptive results of the muscle and bone density of the tibia. Descriptive results for lower limb muscle power and force are also presented.

    Release date: 2021-10-27

  • Articles and reports: 11-522-X202100100005
    Description: The Permanent Census of Population and Housing is the new census strategy adopted in Italy in 2018: it is based on statistical registers combined with data collected through surveys specifically designed to improve registers quality and assure Census outputs. The register at the core of the Permanent Census is the Population Base Register (PBR), whose main administrative sources are the Local Population Registers. The population counts are determined correcting the PBR data with coefficients based on the coverage errors estimated with surveys data, but the need for additional administrative sources clearly emerged while processing the data collected with the first round of Permanent Census. The suspension of surveys due to global-pandemic emergency, together with a serious reduction in census budget for next years, makes more urgent a change in estimation process so to use administrative data as the main source. A thematic register has been set up to exploit all the additional administrative sources: knowledge discovery from this database is essential to extract relevant patterns and to build new dimensions called signs of life, useful for population estimation. The availability of the collected data of the two first waves of Census offers a unique and valuable set for statistical learning: association between surveys results and ‘signs of life’ could be used to build classification model to predict coverage errors in PBR. This paper present the results of the process to produce ‘signs of life’ that proved to be significant in population estimation.

    Key Words: Administrative data; Population Census; Statistical Registers; Knowledge discovery from databases.

    Release date: 2021-10-22

  • Articles and reports: 11-522-X202100100015
    Description: National statistical agencies such as Statistics Canada have a responsibility to convey the quality of statistical information to users. The methods traditionally used to do this are based on measures of sampling error. As a result, they are not adapted to the estimates produced using administrative data, for which the main sources of error are not due to sampling. A more suitable approach to reporting the quality of estimates presented in a multidimensional table is described in this paper. Quality indicators were derived for various post-acquisition processing steps, such as linkage, geocoding and imputation, by estimation domain. A clustering algorithm was then used to combine domains with similar quality levels for a given estimate. Ratings to inform users of the relative quality of estimates across domains were assigned to the groups created. This indicator, called the composite quality indicator (CQI), was developed and experimented with in the Canadian Housing Statistics Program (CHSP), which aims to produce official statistics on the residential housing sector in Canada using multiple administrative data sources.

    Keywords: Unsupervised machine learning, quality assurance, administrative data, data integration, clustering.

    Release date: 2021-10-22

  • Articles and reports: 11-522-X202100100016
    Description: To build data capacity and address the U.S. opioid public health emergency, the National Center for Health Statistics received funding for two projects. The projects involve development of algorithms that use all available structured and unstructured data submitted for the 2016 National Hospital Care Survey (NHCS) to enhance identification of opioid-involvement and the presence of co-occurring disorders (coexistence of a substance use disorder and a mental health issue). A description of the algorithm development process is provided, and lessons learned from integrating data science methods like natural language processing to produce official statistics are presented. Efforts to make the algorithms and analytic datafiles accessible to researchers are also discussed.

    Key Words: Opioids; Co-Occurring Disorders; Data Science; Natural Language Processing; Hospital Care

    Release date: 2021-10-22
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