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All (2,478) (40 to 50 of 2,478 results)

  • 41. A Bias Evaluation for Probabilistic Web Panels at Statistics Canada Archived
    Articles and reports: 11-522-X202500100009
    Description: Three series of web panels were implemented at Statistics Canada from 2020 to 2024. Participants for these web panel series were recruited from respondents of large probabilistic social surveys (recruitment surveys), and subsequently were invited to complete a series of short online surveys. Estimates of recruitment survey variables were calculated using both recruitment survey weights and web panel weights, and these were compared; differences signal the possibility of residual bias that was not corrected by the web panel weighting process. This investigation found more significant differences than would be expected if the web panel estimator fully corrected for the bias resulting from the web panel response process. Questions related to certain topics such as politics and voting, sense of belonging, and media consumption were found to have the most significant differences between web panel estimates and recruitment survey estimates.
    Release date: 2025-09-08
  • 42. Life in the FastText Lane: Harnessing Linear Programming Constrained Machine Learning for Classifications Revision Archived
    Articles and reports: 11-522-X202500100010
    Description: Statistics Canada's Labour Force Survey (LFS) plays an essential role in the estimation of labour market conditions in Canada. Periodically, LFS revises its data to the most recent industry and occupational classification versions. Differences in versions can be extensive, including high-level and unit-group structural changes, creations, deletions, split-offs and combination of classification units (classes). Historically, to reconcile split-off classes - where one class splits into multiple classes - a sample of LFS split-off records would be manually recoded to the new classification version. Based on the split-off proportion observed in the recoded sample, a random allocation method would be applied on all data to reflect the changing Canadian labour market over time. This article proposes using machine learning (fastText), constrained to split-off proportions using linear programming, to revise industry and occupation classifications in LFS. The hybrid framework benefits from a text-based revision mechanism while adhering to traditional proportions driven estimates, thus ensuring a minimal impact on the comparability of published labour market indicators.
    Release date: 2025-09-08
  • 43. Data-driven Imputation Strategies and their Associated Quality Indicators in Economic Surveys Archived
    Articles and reports: 11-522-X202500100011
    Description: The use of modern "data"-driven imputation methods to treat non-response in the context of surveys processed in the Integrated Business Statistics Program at Statistics Canada has previously been explored. It was observed that these methods can lead to high quality imputation and further have the potential to result in broad efficiencies when setting up a particular survey's edit and imputation strategy. However, estimation of the associated total variance, more specifically the component due to imputation, remains a challenge. In this article, two methods for estimation of total variance are proposed and show preliminary results that have motivated us to pursue further research in this area.
    Release date: 2025-09-08
  • 44. The challenges of conducting a survey of youth in Nunavik UVIKKAVUT QANUIPPAT? Archived
    Articles and reports: 11-522-X202500100012
    Description: In 2022, the Institut de la statistique du Québec conducted a survey of high school students in Nunavik, a unique, remote region of Quebec. The survey aimed to develop a portrait of the state of the students' physical and mental health, their lifestyle habits and their environment. This article describes the challenges encountered during the survey and the solutions put in place to overcome them.
    Release date: 2025-09-08
  • 45. Advancing Equitable Data Collection: Insights from Statistics Canada's Statistical Integration Methods Division Disaggregated Data Action Plan Research Project Archived
    Articles and reports: 11-522-X202500100013
    Description: As part of answering the call to action for the United Nations' (UN) 17 Sustainable Development Goals, as well as addressing social, economic, and equity challenges within Canada, Statistics Canada's five-year development phase for the Disaggregated Data Action Plan (DDAP) was funded in 2021 to support data driven decision around these challenges. In turn, the document "Guiding Principles: Leveraging the 2021 Census of Populations Data for DDAP Groups of Interest" were created. The guiding principles document explains the organizational framework of the DDAP in the Agency, describes existing data sources, addresses ethical and privacy concerns, and centralizes sampling methods tailored for DDAP initiatives while accounting for characteristics which can complicate sampling and data collection procedures.
    Release date: 2025-09-08
  • 46. On the Interplay of Legal Requirements, Quality Aspects and Ethical Risks when using Machine Learning in German Official Statistics Archived
    Articles and reports: 11-522-X202500100014
    Description: Artificial intelligence (AI) with its subfield machine learning (ML) has found its way into administration in general and also into official statistics in Germany in particular. This paper highlights the ethical issues that may arise when using AI/ML in official statistics and examines whether a separate ethical framework is needed to deal with these issues appropriately, as is proposed by institutions of other countries and intergovernmental institutions related to official statistics. The results of the study are presented to show that the implementation of the requirements of the existing and mostly non-AI/ML-specific frames of reference such as law and quality is already sufficient to adequately address the ethical issues based on risk scenarios.
    Release date: 2025-09-08
  • 47. Statistical Disclosure Control Analysis for Small Area Estimation Archived
    Articles and reports: 11-522-X202500100015
    Description: Currently, Statistics Canada has no official guidance on confidentiality rules for releasing small area estimate. In recent years, there has been increasing demand from Research Data Centre (RDC) researchers for comprehensive confidentiality guidelines such that they can publish small area estimates in their research. This confidentiality analysis applies to area-level small area estimation.
    Release date: 2025-09-08
  • 48. Synthetic Data Disclosure Risk Assessment: A Literature Review Archived
    Articles and reports: 11-522-X202500100016
    Description: The adoption of synthetic data generation as a confidentiality measure is increasing in statistical agencies worldwide, including at Statistics Canada. This approach provides an alternative to the traditional dissemination of anonymized public microdata files, offering both privacy protection and data utility. However, the creation of synthetic data presents challenges in assessing and mitigating disclosure risks. This paper reviews the different types of disclosure risks, that being attribute, membership and identity disclosure, and presents some of the associated methods for measuring risk. The paper presents prominent risk assessment metrics and discusses practical methods for disclosure control in data synthesis. Methods for assessing disclosure risks usually produce a metric that can be used to gauge the risk, but there is little consensus on threshold values for these metrics. It is also important to focus on importance of balancing utility and confidentiality, which needs further discussion in context of these methods. The paper concludes by offering insights and recommendations about managing disclosure risk while creating synthetic data as well as providing some ideas on future directions for research and practical implications for managing disclosure risks in synthetic data.
    Release date: 2025-09-08
  • 49. Exploration of Deep Learning Synthetic Data Generation for Sensitive Utility Data Sharing Archived
    Articles and reports: 11-522-X202500100017
    Description: Utilities hold crucial information about energy usage and building characteristics which can be utilized by government agencies to improve their corresponding analytics. However, this data is associated with private customer records and thus the building data and energy usage may be too sensitive to share. Often, high-level aggregated versions of this data are shared through robust contracts, limiting the statistics that can be derived. With the advancement of generative machine learning techniques, Statistics Canada and Natural Resources Canada have explored the feasibility of using these models to produce synthetic versions of utility data which may be shared in full to requesting organizations. These synthetic datasets can be created by a utility company through a locally run program and the outputs can be approved before being sent. This work has identified that certain generative models can feasibly be used by utilities to generate new versions of a dataset and has identified the issues which must be addressed prior to implementing this in practice. Both tabular and time-series models have been tested for different data sharing scenarios, where the TimeGAN model successfully captured the general energy peaks and valleys over a given day with reasonable computational requirements. Although this process takes days for annual energy amounts over thousands of customer records, this can enable new data sharing initiatives between utilities and National Statistical Offices while managing privacy risks. As work progresses in future phases with real utility partners, trust can be built for these approaches, and they can begin being tested on real data by actual data holders.
    Release date: 2025-09-08
  • 50. Survey-admin Hybrid Measure of Persistent Child Poverty in New Zealand Archived
    Articles and reports: 11-522-X202500100018
    Description: The Child Poverty Reduction Act (2018) outlines a need for the New Zealand Government to set three- and ten-yearly persistent child poverty reduction targets come end of 2024. In the absence of longitudinal survey data, a survey-administrative data hybrid method that will facilitate the production of these reduction targets and official estimates of persistent child poverty once reporting is required for the 2025/2026 financial year onwards is outlined. This hybrid approach leverages off the cross-sectional Household Economic Survey (HES), administrative-based beneficiary's family data, and recent advances developed for the construction of households within the Administrative Population Census (APC) at Statistics New Zealand. With increasing data collection challenges due to rising non-response and costs, this survey-admin hybrid method represents an alternative to longitudinal survey data collection, ensuring ongoing sustainable and quality statistics to produce persistent child poverty estimates.
    Release date: 2025-09-08
Data (10)

Data (10) ((10 results))

  • 1. Social Policy Simulation Database and Model (SPSD/M)
    Public use microdata: 89F0002X
    Description: The SPSD/M is a static microsimulation model designed to analyse financial interactions between governments and individuals in Canada. It can compute taxes paid to and cash transfers received from government. It is comprised of a database, a series of tax/transfer algorithms and models, analytical software and user documentation.
    Release date: 2026-02-12
  • 2. National Address Register
    Profile of a community or region: 46-26-0002
    Description: The National Address Register (NAR) is a list of commercial and residential addresses in Canada that are extracted from Statistics Canada's Building Register and deemed non-confidential.
    Release date: 2025-12-19
  • 3. PASSAGES microsimulation model
    Table: 89-26-0006
    Description: PASSAGES is an open-source dynamic microsimulation model aimed at supporting policy analysis and research relating to Canadian retirement income system outcomes at the individual and family level. The publicly available version includes a synthetic starting database, a model, and documentation. A confidential starting database is also available.
    Release date: 2025-03-12
  • 4. Canadian Statistical Geospatial Explorer Hub Archived
    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: 2024-08-21
  • 5. Income divergence index (D-index) by census tract
    Table: 11-10-0074-01
    Geography: Census tract
    Frequency: Occasional
    Description:

    The divergence index (D-index) describes the degree that families with different income levels are mixing together in neighbourhoods. It compares neighbourhood (census tract, CT) discrete income distributions to a base distribution, which is the income quintiles of the neighbourhood’s census metropolitan area (CMA).

    Release date: 2020-06-22
  • 6. Housing Data Viewer Archived
    Data Visualization: 71-607-X2019010
    Description: The Housing Data Viewer is a visualization tool that allows users to explore Statistics Canada data on a map. Users can use the tool to navigate, compare and export data.
    Release date: 2019-10-30
  • 7. Findings of the Canadian Vehicle Fuel Pilot Survey Archived
    Table: 53-500-X
    Description:

    This report presents the results of a pilot survey conducted by Statistics Canada to measure the fuel consumption of on-road motor vehicles registered in Canada. This study was carried out in connection with the Canadian Vehicle Survey (CVS) which collects information on road activity such as distance traveled, number of passengers and trip purpose.

    Release date: 2004-10-21
  • 8. National Tourism Indicators, Historical Estimates Archived
    Table: 13-220-X
    Description: In the 1997 edition, new and revised benchmarks were introduced for 1992 and 1988. The indicators are used to monitor supply, demand and employment for tourism in Canada on a timely basis. The annual tables are derived using the National Income and Expenditure Accounts (NIEA) and various industry and travel surveys. Tables providing actual data and percentage changes, for seasonally adjusted current and constant price estimates are included. In addition, an analytical section provides graphs, and time series of first differences, percentage changes, and seasonal factors for selected indicators. Data are published from 1987 and the publication will be available on the day of release. New data are included in the demand tables for non-tourism commodities produced by non-tourism industries and in the employment tables covering direct tourism employment generated by non-tourism industries. This product was commissioned by the Canadian Tourism Commission to provide annual updates for the Tourism Satellite Account.
    Release date: 2003-01-08
  • 9. Historical Statistics of Canada Archived
    Table: 11-516-X
    Description:

    The second edition of Historical statistics of Canada was jointly produced by the Social Science Federation of Canada and Statistics Canada in 1983. This volume contains about 1,088 statistical tables on the social, economic and institutional conditions of Canada from the start of Confederation in 1867 to the mid-1970s. The tables are arranged in sections with an introduction explaining the content of each section, the principal sources of data for each table, and general explanatory notes regarding the statistics. In most cases, there is sufficient description of the individual series to enable the reader to use them without consulting the numerous basic sources referenced in the publication.

    The electronic version of this historical publication is accessible on the Internet site of Statistics Canada as a free downloadable document: text as HTML pages and all tables as individual spreadsheets in a comma delimited format (CSV) (which allows online viewing or downloading).

    Release date: 1999-07-29
  • 10. National Population Health Survey Overview Archived
    Table: 82-567-X
    Description:

    The National Population Health Survey (NPHS) is designed to enhance the understanding of the processes affecting health. The survey collects cross-sectional as well as longitudinal data. In 1994/95 the survey interviewed a panel of 17,276 individuals, then returned to interview them a second time in 1996/97. The response rate for these individuals was 96% in 1996/97. Data collection from the panel will continue for up to two decades. For cross-sectional purposes, data were collected for a total of 81,000 household residents in all provinces (except people on Indian reserves or on Canadian Forces bases) in 1996/97.

    This overview illustrates the variety of information available by presenting data on perceived health, chronic conditions, injuries, repetitive strains, depression, smoking, alcohol consumption, physical activity, consultations with medical professionals, use of medications and use of alternative medicine.

    Release date: 1998-07-29
Analysis (2,036)

Analysis (2,036) (40 to 50 of 2,036 results)

  • 41. Survey-admin Hybrid Measure of Persistent Child Poverty in New Zealand Archived
    Articles and reports: 11-522-X202500100018
    Description: The Child Poverty Reduction Act (2018) outlines a need for the New Zealand Government to set three- and ten-yearly persistent child poverty reduction targets come end of 2024. In the absence of longitudinal survey data, a survey-administrative data hybrid method that will facilitate the production of these reduction targets and official estimates of persistent child poverty once reporting is required for the 2025/2026 financial year onwards is outlined. This hybrid approach leverages off the cross-sectional Household Economic Survey (HES), administrative-based beneficiary's family data, and recent advances developed for the construction of households within the Administrative Population Census (APC) at Statistics New Zealand. With increasing data collection challenges due to rising non-response and costs, this survey-admin hybrid method represents an alternative to longitudinal survey data collection, ensuring ongoing sustainable and quality statistics to produce persistent child poverty estimates.
    Release date: 2025-09-08
  • 42. Efficient Record Linkage for Large Datasets by Business Names Archived
    Articles and reports: 11-522-X202500100019
    Description: Accurate and efficient record linkage is crucial for maintaining a comprehensive and current Statistical Business Register (SBR) at Statistics Canada. Linking external business lists to the SBR by name presents computational and methodological challenges, especially as data volumes grow. This paper describes a scalable methodology that employs blocking techniques to constrain the computational search space and integrates multiple similarity measures—from edit distances and n-gram overlaps to embedding-based methods using Sentence-BERT (SBERT)—to identify likely matches. By combining simple character-level comparisons with more advanced semantic embedding methods, the approach can adapt to various naming conventions and complexities. While it does not guarantee superior accuracy in all circumstances, it offers a pragmatic balance between computational feasibility and linkage quality.
    Release date: 2025-09-08
  • 43. Evaluating the Accuracy when Linking Records in Waves Archived
    Articles and reports: 11-522-X202500100020
    Description: At Statistics Canada, many data sets are linked with quasi-identifiers such as the first name, last name, or address. In such cases, linkage errors are a potential concern and must be measured. In that regard, previous studies have shown that the evaluation may be based on modeling the number of links from a given record while accounting for all the interactions among the linkage variables and dispensing with clerical reviews, so long as the decision to link two records does not involve other records. In this communication, the methodology is adapted for a class of practical strategies, which violate this constraint by linking the records in consecutive waves, where a given wave links a subset of the records that are not linked in previous waves. In particular, the linkage may be based on a deterministic wave followed by a probabilistic one.
    Release date: 2025-09-08
  • 44. Model-Based Threshold Selection for Agricultural Linkages Archived
    Articles and reports: 11-522-X202500100021
    Description: Optimal threshold selection is a critical challenge in probabilistic linkage, with significant implications for the accuracy and reliability of linked datasets. This paper analyzes the performance of the neighbour model, a recently proposed error model which models linkage errors by the number of links from each record. Three threshold selection algorithms utilizing the neighbour model were assessed, highlighting the strengths and limitations of each. Their performance was assessed through simulation studies, which demonstrated that methods using the neighbour model achieved lower relative bias compared to two established methods for threshold selection. Additionally, the practical utility was validated through goodness-of-fit tests conducted on four agricultural datasets, showing the potential of the model for use in real-world applications.
    Release date: 2025-09-08
  • 45. T1 Redesign: T1 Partnership Identification Process Archived
    Articles and reports: 11-522-X202500100022
    Description: In Canada, T1 Tax forms are used to report personal income, whether earned as an employee or through self-employment. Income from self-employment, or "T1 Business Income" is reported by sole proprietorships or partnerships. A T1 partnership involves two or more legal entities jointly filing for a shared business. T1 business data is received as individual filings, meaning partnerships are received separately for each partner. Internal record linkage within the T1 business database is performed to identify partnerships and prevent overcoverage within the final population of T1 businesses. This new T1 partnership identification process takes advantage of newer algorithms, such as DBSCAN numerical clustering fuzzy matching, to identify internal linkages. Graph theory is used to construct the list of partnerships from the row-pairs identified in the linkage process.
    Release date: 2025-09-08
  • 46. Development of Linkage-Adjusted Weights Accounting for Gender for the 2021 Canadian Census Health and Environment Cohort Archived
    Articles and reports: 11-522-X202500100023
    Description: The latest Canadian Census Health and Environment Cohort (CanCHEC) continues a series of population-based microdata linkages focused on population health research by demographic, social and economic characteristics. The 2021 CanCHEC consists of 95.5% of the 2021 Census long-form sample survey records. The records of survey respondents that could not be linked to the Derived Record Depository and those presumed to be duplicates account for the remaining 4.5%. Linkage-adjusted main and replicate weights allow researchers to estimate and evaluate the variance of summary measures about population health in the presence of missed linked pairs to better understand the experiences of diverse population groups.
    Release date: 2025-09-08
  • 47. The Future of National Statistical Organisations: The Longer-Term Role and Shape of NSOs Archived
    Articles and reports: 11-522-X202500100024
    Description: This paper explores a vision for the future of National Statistics Offices (NSOs). It analyses the history and role of NSOs before exploring current and future challenges and opportunities for NSOs, before finally outlining a future where NSOs become more agile, open, and collaborative while maintaining their high level of trust in the community, thereby allowing them to fulfil their new role as data stewards in a rapidly evolving data landscape.
    Release date: 2025-09-08
  • 48. Statistical Inference for a Finite Population Mean with Machine Learning-Based Imputation for Missing Survey Data Archived
    Articles and reports: 11-522-X202500100025
    Description: National statistical offices have increasingly adopted machine learning (ML) for its potential to improve survey estimates. ML techniques offer significant advantages, notably the ability to manage high-dimensional data and to capture complex, nonlinear relationships, thereby enhancing the overall quality of survey statistics. In this article, following the approach of Chernozhukov et al. (2018), we describe a double debiased machine learning framework that enables valid statistical inference when imputed estimators are derived from ML procedures. Simulation results suggest that the proposed framework performs well in a wide range of scenarios.
    Release date: 2025-09-08
  • 49. A Safe and Inclusive Approach to Disseminating Statistical Information about the Non-binary Population in Canada Archived
    Articles and reports: 11-522-X202500100026
    Description: In 2022, Canada became the first country to release statistical information about its transgender and non-binary populations based on census data. Moreover, following a 2018 government-wide policy direction, Statistics Canada's surveys have been collecting and disseminating information about gender by default rather than sex at birth. Due to the small size of the transgender and non-binary populations, disseminating safe statistical information about them at detailed geographical levels poses a challenge.
    Release date: 2025-09-08
  • 50. One-Stop-Shop for Artificial Intelligence and Machine Learning for Official Statistics Archived
    Articles and reports: 11-522-X202500100027
    Description: Several challenges encountered when constructing U.S. administrative record-based (AR-based) population estimates for 2020 are identified. They include locational accuracy, person coverage and its consistency over time, filtering out non-residents and people not alive on the reference date, uncovering missing links across person and address records, and predicting demographic characteristics. Several ways to address these issues are discussed. Regression results illustrate how the challenges and solutions affect the AR-based county population estimates.
    Release date: 2025-09-08
Reference (380)

Reference (380) (20 to 30 of 380 results)

  • 21. Methods for Constructing Life Tables for Canada, Provinces and Territories
    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
  • 22. Agriculture–Population Linkage: Data quality report
    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
  • 23. Aggregated and derived income concepts and income statistics, 2021 Census of Population
    Surveys and statistical programs – Documentation: 98-20-00032021011
    Description: This video explains the key concepts of different levels of aggregation of income data such as household and family income; income concepts derived from key income variables such as adjusted income and equivalence scale; and statistics used for income data such as median and average income, quartiles, quintiles, deciles and percentiles.
    Release date: 2023-03-29
  • 24. Low-income concepts and statistics, 2021 Census of Population
    Surveys and statistical programs – Documentation: 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
  • 25. Longitudinal Immigration Database (IMDB) Technical Report, 2021
    Surveys and statistical programs – Documentation: 11-633-X2022009
    Description: The Longitudinal Immigration Database (IMDB) is a comprehensive source of data that plays a key role in the understanding of the economic behaviour of immigrants. It is the only annual Canadian dataset that allows users to study the characteristics of immigrants to Canada at the time of admission and their economic outcomes and regional (inter-provincial) mobility over a time span of more than 35 years.

    This report will discuss the IMDB data sources, concepts and variables, record linkage, data processing, dissemination, data evaluation and quality indicators, comparability with other immigration datasets, and the analyses possible with the IMDB.

    Release date: 2022-12-05
  • 26. Guide to the Census of Agriculture
    Surveys and statistical programs – Documentation: 32-26-0002
    Description: This reference guide may be useful to both new and experienced users who wish to familiarize themselves with and find specific information about the Census of Agriculture.

    It provides an overview of the Census of Agriculture communications, content determination, collection, processing, data quality evaluation and dissemination activities. It also summarizes the key changes to the census and other useful information.

    Release date: 2022-04-14
  • 27. Standard Geographical Classification (SGC) Volume II. Reference Maps
    Geographic files and documentation: 12-572-X
    Description:

    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 II contains reference maps showing boundaries, names, codes and locations of the geographic areas in the classification. The reference maps show census subdivisions, census divisions, census metropolitan areas, census agglomerations, census metropolitan influenced zones and economic regions. Definitions for these terms are found in Volume I, The Classification. Volume I describes the classification and related standard geographic areas and place names.

    The maps in Volume II can be downloaded in PDF format from our website.

    Release date: 2022-02-09
  • 28. Longitudinal Immigration Database (IMDB) Technical Report, 2020
    Surveys and statistical programs – Documentation: 11-633-X2021008
    Description: The Longitudinal Immigration Database (IMDB) is a comprehensive source of data that plays a key role in the understanding of the economic behaviour of immigrants. It is the only annual Canadian dataset that allows users to study the characteristics of immigrants to Canada at the time of admission and their economic outcomes and regional (inter-provincial) mobility over a time span of more than 35 years. The IMDB includes Immigration, Refugees and Citizenship Canada (IRCC) administrative records which contain exhaustive information about immigrants who were admitted to Canada since 1952. It also includes data about non-permanent residents who have been issued temporary resident permits since 1980. This report will discuss the IMDB data sources, concepts and variables, record linkage, data processing, dissemination, data evaluation and quality indicators, comparability with other immigration datasets, and the analyses possible with the IMDB.
    Release date: 2021-12-06
  • 29. Statistics: Power from Data!
    Surveys and statistical programs – Documentation: 12-004-X
    Description:

    Statistics: Power from Data! is a web resource that was created in 2001 to assist secondary students and teachers of Mathematics and Information Studies in getting the most from statistics. Over the past 20 years, this product has become one of Statistics Canada most popular references for students, teachers, and many other members of the general population. This product was last updated in 2021.

    Release date: 2021-09-02
  • 30. Multi-year Consolidated Plan for Research, Modelling and Data Development, 2021 to 2023 Archived
    Surveys and statistical programs – Documentation: 11-633-X2021005
    Description:

    The Analytical Studies and Modelling Branch (ASMB) is the research arm of Statistics Canada mandated 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 broad range of data sources and modelling techniques to address the information needs of a broad range of government, academic and public sector partners and stakeholders through analysis and research, modeling and predictive analytics, and data development. The branch strives to deliver relevant, high-quality, timely, comprehensive, horizontal and integrated research and to enable the use of its research through capacity building and strategic dissemination to meet the user needs of policy makers, academics and the general public.

    This Multi-year Consolidated Plan for Research, Modelling and Data Development outlines the priorities for the branch over the next two years.

    Release date: 2021-08-12

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