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All (180) (0 to 10 of 180 results)

1. Interpreting population totals from the Labour Force Survey
Articles and reports: 75-005-M2024004
Description: This article provides information about population totals in the Labour Force Survey (LFS), including details on who is included in the survey target population, and a description of the methodology used to produce monthly population totals in the LFS. The note also provides guidance on how to interpret population statistics in the LFS, and discusses the extent to which the LFS can be used to examine disaggregated labour market indicators for new immigrants and non-permanent residents.
Release date: 2024-09-20
2. Analytical Studies: Methods and References
Journals and periodicals: 11-633-X
Description: Papers in this series provide background discussions of the methods used to develop data for economic, health, and social analytical studies at Statistics Canada. They are intended to provide readers with information on the statistical methods, standards and definitions used to develop databases for research purposes. All papers in this series have undergone peer and institutional review to ensure that they conform to Statistics Canada's mandate and adhere to generally accepted standards of good professional practice.
Release date: 2024-09-11
3. Reconstruction attack risk using Statistics Canada Census Data Archived
Articles and reports: 11-522-X202200100008
Description: The publication of more disaggregated data can increase transparency and provide important information on underrepresented groups. Developing more readily available access options increases the amount of information available to and produced by researchers. Increasing the breadth and depth of the information released allows for a better representation of the Canadian population, but also puts a greater responsibility on Statistics Canada to do this in a way that preserves confidentiality, and thus it is helpful to develop tools which allow Statistics Canada to quantify the risk from the additional data granularity. In an effort to evaluate the risk of a database reconstruction attack on Statistics Canada’s published Census data, this investigation follows the strategy of the US Census Bureau, who outlined a method to use a Boolean satisfiability (SAT) solver to reconstruct individual attributes of residents of a hypothetical US Census block, based just on a table of summary statistics. The technique is expanded to attempt to reconstruct a small fraction of Statistics Canada’s Census microdata. This paper will discuss the findings of the investigation, the challenges involved in mounting a reconstruction attack, and the effect of an existing confidentiality measure in mitigating these attacks. Furthermore, the existing strategy is compared to other potential methods used to protect data – in particular, releasing tabular data perturbed by some random mechanism, such as those suggested by differential privacy.
Release date: 2024-03-25
4. Evaluating sampling methods for ethnic minorities Archived
Articles and reports: 11-522-X202200100014
Description: Ethnic minorities are often underrepresented in survey research, due to the challenges many researchers face in including these populations. While some studies discuss several methods in comparison, few have directly compared these methods empirically, leaving researchers seeking to include ethnic minorities in their studies unsure of their best options. In this article, I briefly review the methodological and ethical reasons for increasing ethnic minority representation in social science research, as well as challenges of doing so. I then present findings from ten studies which empirically compare methods of sampling and/or recruiting ethnic minority individuals. Finally, I discuss some implications for future research.
Release date: 2024-03-25
5. Dealing with undercoverage for non-probability survey samples
Articles and reports: 12-001-X202300200005
Description: Population undercoverage is one of the main hurdles faced by statistical analysis with non-probability survey samples. We discuss two typical scenarios of undercoverage, namely, stochastic undercoverage and deterministic undercoverage. We argue that existing estimation methods under the positivity assumption on the propensity scores (i.e., the participation probabilities) can be directly applied to handle the scenario of stochastic undercoverage. We explore strategies for mitigating biases in estimating the mean of the target population under deterministic undercoverage. In particular, we examine a split population approach based on a convex hull formulation, and construct estimators with reduced biases. A doubly robust estimator can be constructed if a followup subsample of the reference probability survey with measurements on the study variable becomes feasible. Performances of six competing estimators are investigated through a simulation study and issues which require further investigation are briefly discussed.
Release date: 2024-01-03
6. Mapping Production Activity in Yukon: Experimental Indexes of Grid Square-based Gross Domestic Product
Articles and reports: 11-633-X2023003
Description: This paper spans the academic work and estimation strategies used in national statistics offices. It addresses the issue of producing fine, grid-level geography estimates for Canada by exploring the measurement of subprovincial and subterritorial gross domestic product using Yukon as a test case.
Release date: 2023-12-15
7. One-sided testing of population domain means in surveys
Articles and reports: 12-001-X202300100001
Description: Recent work in survey domain estimation allows for estimation of population domain means under a priori assumptions expressed in terms of linear inequality constraints. For example, it might be known that the population means are non-decreasing along ordered domains. Imposing the constraints has been shown to provide estimators with smaller variance and tighter confidence intervals. In this paper we consider a formal test of the null hypothesis that all the constraints are binding, versus the alternative that at least one constraint is non-binding. The test of constant versus increasing domain means is a special case. The power of the test is substantially better than the test with the same null hypothesis and an unconstrained alternative. The new test is used with data from the National Survey of College Graduates, to show that salaries are positively related to the subject’s father’s educational level, across fields of study and over several years of cohorts.
Release date: 2023-06-30
8. Survey data integration for regression analysis using model calibration
Articles and reports: 12-001-X202300100002
Description: We consider regression analysis in the context of data integration. To combine partial information from external sources, we employ the idea of model calibration which introduces a “working” reduced model based on the observed covariates. The working reduced model is not necessarily correctly specified but can be a useful device to incorporate the partial information from the external data. The actual implementation is based on a novel application of the information projection and model calibration weighting. The proposed method is particularly attractive for combining information from several sources with different missing patterns. The proposed method is applied to a real data example combining survey data from Korean National Health and Nutrition Examination Survey and big data from National Health Insurance Sharing Service in Korea.
Release date: 2023-06-30
9. Sustainable Development Goals: Goal 7, Affordable and Clean Energy
Articles and reports: 11-637-X202200100007
Description:
As the seventh goal outlined in the 2030 Agenda for Sustainable Development, Canada and other UN member states have committed to ensure access to affordable, reliable, sustainable and modern energy for all by 2030. This 2022 infographic provides an overview of indicators underlying the seventh Sustainable Development Goal in support of affordable and clean energy, and the statistics and data sources used to monitor and report on this goal in Canada.

Release date: 2022-12-13
10. Sustainable Development Goals: Goal 8, Decent Work and Economic Growth
Articles and reports: 11-637-X202200100008
Description:
As the eighth goal outlined in the 2030 Agenda for Sustainable Development, Canada and other UN member states have committed to promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all by 2030. This 2022 infographic provides an overview of indicators underlying the eighth Sustainable Development Goal in support of decent work and economic growth, and the statistics and data sources used to monitor and report on this goal in Canada.

Release date: 2022-12-13

Stats in brief (15)

Stats in brief (15) (0 to 10 of 15 results)

1. Data ethics part 2: Ethical reviews Archived
Stats in brief: 89-20-00062022004
Description:
Gathering, exploring, analyzing and interpreting data are essential steps in producing information that benefits society, the economy and the environment. In this video, we will discuss the importance of considering data ethics throughout the process of producing statistical information.

As a pre-requisite to this video, make sure to watch the video titled “Data Ethics: An introduction” also available in Statistics Canada’s data literacy training catalogue.

Release date: 2022-10-17
2. Statistics 101: Statistical Bias Archived
Stats in brief: 89-20-00062022005
Description:
In this video, you will learn the answers to the following questions: What are the different types of error? What are the types of error that lead to statistical bias? Where during the data journey statistical bias can occur?

Release date: 2022-10-17
3. Data ethics: An introduction Archived
Stats in brief: 89-20-00062022001
Description:
Gathering, exploring, analyzing and interpreting data are essential steps in producing information that benefits society, the economy and the environment. To properly conduct these processes, data ethics ethics must be upheld in order to ensure the appropriate use of data.

Release date: 2022-05-24
4. FAIR data principles: What is FAIR? Archived
Stats in brief: 89-20-00062022002
Description:
This video will break down what it means to be FAIR in terms of data and metadata, and how each pillar of FAIR serves to guide data users and producers alike, as they navigate their way through the data journey, in order to gain maximum, long term value.

Release date: 2022-05-24
5. Statistics 101: Confidence intervals Archived
Stats in brief: 89-20-00062022003
Description:
By the end of this video you will understand what confidence intervals are, why we use them, and what factors have an impact on them.

Release date: 2022-05-24
6. Study: A 30-year look at the work histories of Canadian workers Archived
Stats in brief: 11-001-X202134332266
Description: Release published in The Daily – Statistics Canada’s official release bulletin
Release date: 2021-12-09
7. Framework for Responsible Machine Learning Processes at Statistics Canada Archived
Stats in brief: 89-20-00062021001
Description:
As Canada's national statistical organization, Statistics Canada is committed to sharing our knowledge and expertise to help all Canadians develop their data literacy skills. The goal is to provide learners with information on the basic concepts and skills with regard to a range of data literacy topics.
The training is aimed at those who are new to data or those who have some experience with data but may need a refresher or want to expand their knowledge. We invite you to check out our Learning catalogue to learn more about our offerings including a great collection of short videos. Be sure to check back regularly as we will be continuing to release new training.
Release date: 2021-05-03
8. Statistics 101: Proportions, ratios, and rates Archived
Stats in brief: 89-20-00062021003
Description:
In this video, viewers will learn the differences between three types of measure: proportions, ratios, and rates. In addition, viewers by the end of this video will be able to determine how each measure is calculated and when it is best to use one measure rather than the other.

Release date: 2021-05-03
9. Machine learning: An introduction Archived
Stats in brief: 89-20-00062021004
Description:
One important distinction we will make in this video is the differences between Data Science, Artificial Intelligence and Machine Learning. You'll learn what machine learning can be used for, how it works, and some different methods for doing it. And you'll also learn how to build and use machine learning processes responsibly.
This video is recommended for those who already have some familiarity with the concepts and techniques associated with computer programming and using algorithms to analyze data.
Release date: 2021-05-03
10. Telling the data story: How to create stories that matter Archived
Stats in brief: 89-20-00062021005
Description:
By the end of this video, you should have a deeper understanding of the fundamentals of using data to tell a story. We will go over some the principle components of storytelling including the data, the narrative and visualization, and discuss how they can be used to construct concise, informative and interesting messages your audience can trust. And then, you will learn the importance of a well planned data story, which includes learning who your audience will be, what they should know and how to best deliver that information.
Release date: 2021-05-03

Articles and reports (163)

Articles and reports (163) (0 to 10 of 163 results)

1. Interpreting population totals from the Labour Force Survey
Articles and reports: 75-005-M2024004
Description: This article provides information about population totals in the Labour Force Survey (LFS), including details on who is included in the survey target population, and a description of the methodology used to produce monthly population totals in the LFS. The note also provides guidance on how to interpret population statistics in the LFS, and discusses the extent to which the LFS can be used to examine disaggregated labour market indicators for new immigrants and non-permanent residents.
Release date: 2024-09-20
2. Reconstruction attack risk using Statistics Canada Census Data Archived
Articles and reports: 11-522-X202200100008
Description: The publication of more disaggregated data can increase transparency and provide important information on underrepresented groups. Developing more readily available access options increases the amount of information available to and produced by researchers. Increasing the breadth and depth of the information released allows for a better representation of the Canadian population, but also puts a greater responsibility on Statistics Canada to do this in a way that preserves confidentiality, and thus it is helpful to develop tools which allow Statistics Canada to quantify the risk from the additional data granularity. In an effort to evaluate the risk of a database reconstruction attack on Statistics Canada’s published Census data, this investigation follows the strategy of the US Census Bureau, who outlined a method to use a Boolean satisfiability (SAT) solver to reconstruct individual attributes of residents of a hypothetical US Census block, based just on a table of summary statistics. The technique is expanded to attempt to reconstruct a small fraction of Statistics Canada’s Census microdata. This paper will discuss the findings of the investigation, the challenges involved in mounting a reconstruction attack, and the effect of an existing confidentiality measure in mitigating these attacks. Furthermore, the existing strategy is compared to other potential methods used to protect data – in particular, releasing tabular data perturbed by some random mechanism, such as those suggested by differential privacy.
Release date: 2024-03-25
3. Evaluating sampling methods for ethnic minorities Archived
Articles and reports: 11-522-X202200100014
Description: Ethnic minorities are often underrepresented in survey research, due to the challenges many researchers face in including these populations. While some studies discuss several methods in comparison, few have directly compared these methods empirically, leaving researchers seeking to include ethnic minorities in their studies unsure of their best options. In this article, I briefly review the methodological and ethical reasons for increasing ethnic minority representation in social science research, as well as challenges of doing so. I then present findings from ten studies which empirically compare methods of sampling and/or recruiting ethnic minority individuals. Finally, I discuss some implications for future research.
Release date: 2024-03-25
4. Dealing with undercoverage for non-probability survey samples
Articles and reports: 12-001-X202300200005
Description: Population undercoverage is one of the main hurdles faced by statistical analysis with non-probability survey samples. We discuss two typical scenarios of undercoverage, namely, stochastic undercoverage and deterministic undercoverage. We argue that existing estimation methods under the positivity assumption on the propensity scores (i.e., the participation probabilities) can be directly applied to handle the scenario of stochastic undercoverage. We explore strategies for mitigating biases in estimating the mean of the target population under deterministic undercoverage. In particular, we examine a split population approach based on a convex hull formulation, and construct estimators with reduced biases. A doubly robust estimator can be constructed if a followup subsample of the reference probability survey with measurements on the study variable becomes feasible. Performances of six competing estimators are investigated through a simulation study and issues which require further investigation are briefly discussed.
Release date: 2024-01-03
5. Mapping Production Activity in Yukon: Experimental Indexes of Grid Square-based Gross Domestic Product
Articles and reports: 11-633-X2023003
Description: This paper spans the academic work and estimation strategies used in national statistics offices. It addresses the issue of producing fine, grid-level geography estimates for Canada by exploring the measurement of subprovincial and subterritorial gross domestic product using Yukon as a test case.
Release date: 2023-12-15
6. One-sided testing of population domain means in surveys
Articles and reports: 12-001-X202300100001
Description: Recent work in survey domain estimation allows for estimation of population domain means under a priori assumptions expressed in terms of linear inequality constraints. For example, it might be known that the population means are non-decreasing along ordered domains. Imposing the constraints has been shown to provide estimators with smaller variance and tighter confidence intervals. In this paper we consider a formal test of the null hypothesis that all the constraints are binding, versus the alternative that at least one constraint is non-binding. The test of constant versus increasing domain means is a special case. The power of the test is substantially better than the test with the same null hypothesis and an unconstrained alternative. The new test is used with data from the National Survey of College Graduates, to show that salaries are positively related to the subject’s father’s educational level, across fields of study and over several years of cohorts.
Release date: 2023-06-30
7. Survey data integration for regression analysis using model calibration
Articles and reports: 12-001-X202300100002
Description: We consider regression analysis in the context of data integration. To combine partial information from external sources, we employ the idea of model calibration which introduces a “working” reduced model based on the observed covariates. The working reduced model is not necessarily correctly specified but can be a useful device to incorporate the partial information from the external data. The actual implementation is based on a novel application of the information projection and model calibration weighting. The proposed method is particularly attractive for combining information from several sources with different missing patterns. The proposed method is applied to a real data example combining survey data from Korean National Health and Nutrition Examination Survey and big data from National Health Insurance Sharing Service in Korea.
Release date: 2023-06-30
8. Sustainable Development Goals: Goal 7, Affordable and Clean Energy
Articles and reports: 11-637-X202200100007
Description:
As the seventh goal outlined in the 2030 Agenda for Sustainable Development, Canada and other UN member states have committed to ensure access to affordable, reliable, sustainable and modern energy for all by 2030. This 2022 infographic provides an overview of indicators underlying the seventh Sustainable Development Goal in support of affordable and clean energy, and the statistics and data sources used to monitor and report on this goal in Canada.

Release date: 2022-12-13
9. Sustainable Development Goals: Goal 8, Decent Work and Economic Growth
Articles and reports: 11-637-X202200100008
Description:
As the eighth goal outlined in the 2030 Agenda for Sustainable Development, Canada and other UN member states have committed to promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all by 2030. This 2022 infographic provides an overview of indicators underlying the eighth Sustainable Development Goal in support of decent work and economic growth, and the statistics and data sources used to monitor and report on this goal in Canada.

Release date: 2022-12-13
10. Sustainable Development Goals: Goal 9, Industry, Innovation and Infrastructure
Articles and reports: 11-637-X202200100009
Description:
As the ninth goal outlined in the 2030 Agenda for Sustainable Development, Canada and other UN member states have committed to build resilient infrastructure, promote inclusive and sustainable industrialization and foster innovation by 2030. This 2022 infographic provides an overview of indicators underlying the ninth Sustainable Development Goal in support of industry, innovation and infrastructure, and the statistics and data sources used to monitor and report on this goal in Canada.

Release date: 2022-12-13

Journals and periodicals (2)

Journals and periodicals (2) ((2 results))

1. Analytical Studies: Methods and References
Journals and periodicals: 11-633-X
Description: Papers in this series provide background discussions of the methods used to develop data for economic, health, and social analytical studies at Statistics Canada. They are intended to provide readers with information on the statistical methods, standards and definitions used to develop databases for research purposes. All papers in this series have undergone peer and institutional review to ensure that they conform to Statistics Canada's mandate and adhere to generally accepted standards of good professional practice.
Release date: 2024-09-11
2. Validation Study for a Record Linkage of Births and Infant Deaths in Canada Archived
Journals and periodicals: 84F0013X
Geography: Canada, Province or territory
Description:
This study was initiated to test the validity of probabilistic linkage methods used at Statistics Canada. It compared the results of data linkages on infant deaths in Canada with infant death data from Nova Scotia and Alberta. It also compared the availability of fetal deaths on the national and provincial files.
Release date: 1999-10-08

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Date modified:: 2024-10-18

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