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All (105) (20 to 30 of 105 results)

  • 21. Collaborative Data Science within Government of Canada: Development of R libraries for common tasks with Open Canada data Archived
    Articles and reports: 11-522-X202100100028
    Description:

    Many Government of Canada groups are developing codes to process and visualize various kinds data, often duplicating each other’s efforts, with sub-optimal efficiency and limited level of code quality reviewing. This paper informally presents a working-level approach to addressing this technical problem. The idea is to collaboratively build a common repository of code and knowledgebase for use by anyone in the public sector to perform many common data science tasks, and, in doing that, help each other to master both the data science coding skills and the industry standard collaborative practices. The paper explains why R language is used as the language of choice for collaborative data science code development. It summaries R advantages and addresses its limitations, establishes the taxonomy of discussion topics of highest interested to the GC data scientists working with R, provides an overview of used collaborative platforms, and presents the results obtained to date. Even though the code knowledgebase is developed mainly in R, it is meant to be valuable also for data scientists coding in Python and other development environments. Key Words: Collaboration; Data science; Data Engineering; R; Open Government; Open Data; Open Science

    Release date: 2021-10-29
  • 22. Survey Data Integration for Regression Analysis Using Model Calibration Archived
    Articles and reports: 11-522-X202100100001
    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 empirical likelihood method. 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.

    Key Words: Big data; Empirical likelihood; Measurement error models; Missing covariates.

    Release date: 2021-10-15
  • 23. Responsible use of machine learning at Statistics Canada Archived
    Articles and reports: 11-522-X202100100002
    Description:

    A framework for the responsible use of machine learning processes has been developed at Statistics Canada. The framework includes guidelines for the responsible use of machine learning and a checklist, which are organized into four themes: respect for people, respect for data, sound methods, and sound application. All four themes work together to ensure the ethical use of both the algorithms and results of machine learning. The framework is anchored in a vision that seeks to create a modern workplace and provide direction and support to those who use machine learning techniques. It applies to all statistical programs and projects conducted by Statistics Canada that use machine learning algorithms. This includes supervised and unsupervised learning algorithms. The framework and associated guidelines will be presented first. The process of reviewing projects that use machine learning, i.e., how the framework is applied to Statistics Canada projects, will then be explained. Finally, future work to improve the framework will be described.

    Keywords: Responsible machine learning, explainability, ethics

    Release date: 2021-10-15
  • 24. Predicting transitions into and out of poverty using machine learning Archived
    Articles and reports: 11-522-X202100100003
    Description:

    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
  • 25. Modernizing Construction Indicators Through Machine Learning and Satellite Imagery Archived
    Articles and reports: 11-522-X202100100019
    Description: Official statistical agencies must continually seek new methods and techniques that can increase both program efficiency and product relevance. The U.S. Census Bureau’s measurement of construction activity is currently a resource-intensive endeavor, relying heavily on monthly survey response via questionnaires and extensive field data collection. While our data users continually require more timely and granular data products, the traditional survey approach and associated collection cost and respondent burden limits our ability to meet that need. In 2019, we began research on whether the application of machine learning techniques to satellite imagery could accurately estimate housing starts and completions while meeting existing monthly indicator timelines at a cost equal to or less than existing methods. Using historical Census construction survey data in combination with targeted satellite imagery, the team trained, tested, and validated convolutional neural networks capable of classifying images by their stage of construction demonstrating the viability of a data science-based approach to producing official measures of construction activity.

    Key Words: Official Statistics; Housing Starts, Machine Learning, Satellite Imagery

    Release date: 2021-10-15
  • 26. Statistics 101: Exploring measures of central tendency Archived
    Stats in brief: 89-20-00062020002
    Description:

    This video is intended to teach viewers the differences between three fundamental statistical concepts. First, the mean, then the median and finally, the mode.

    Release date: 2021-05-03
  • 27. Statistics 101: Exploring measures of dispersion Archived
    Stats in brief: 89-20-00062020003
    Description:

    In this module, we will explore the concept of dispersion, also called variability. This concept includes: the range, the interquartile range, the standard deviation and the normal distribution.

    Release date: 2021-05-03
  • 28. Study: Measuring proximity to services and amenities Archived
    Stats in brief: 11-001-X202104628783
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2021-02-15
  • 29. Measuring proximity to services and amenities: An experimental set of indicators for neighbourhoods and localities
    Articles and reports: 18-001-X2020001
    Description:

    This paper presents the methodology used to generate the first nationwide database of proximity measures and the results obtained with a first set of ten measures. The computational methods are presented as a generalizable model due to the fact that it is now possible to apply similar methods to a multitude of other services or amenities, in a variety of alternative specifications.

    Release date: 2021-02-15
  • 30. Statistical standards: A national research and development standard Archived
    Stats in brief: 11-627-M2020072
    Description:

    This infographic provides an overview of the Canadian Research and Development Classification (CRDC), a national standard jointly developed by the Canada Foundation for Innovation (CFI), the Canadian Institutes of Health Research (CIHR), the Natural Sciences and Engineering Research Council of Canada (NSERC), the Social Sciences and Humanities Research Council of Canada (SSHRC), and Statistics Canada.

    Release date: 2020-10-05
Stats in brief (18)

Stats in brief (18) (0 to 10 of 18 results)

  • 1. The Importance of Disaggregated Data: An Introduction (part 1)
    Stats in brief: 89-20-00062024001
    Description: This short video explains how it can be very effective for all levels of governments and organizations that serve communities to use disaggregated data to make evidence-informed public policy decisions. By using disaggregated data, policymakers are able to design more appropriate and effective policies that meet the needs of each diverse and unique Canadian.
    Release date: 2024-07-16
  • 2. The Importance of Disaggregated Data: An Introduction (part 2)
    Stats in brief: 89-20-00062024002
    Description: This short video explains how the use of disaggregated data can help policymakers to develop more targeted and effective policies by identifying the unique needs and challenges faced by different demographic groups.
    Release date: 2024-07-16
  • 3. Created Equal
    Stats in brief: 45-20-00032022002
    Description:

    Canada’s diversity and rich cultural heritage have been shaped by the people who have come from all over the world to call it home. But even in our multicultural society, eliminating all forms of discrimination remains a challenge. In this episode, we turn a critical eye to the ways that cognitive bias risks perpetuating systemic racism. Statistics are supposed to accurately reflect the world around us, but are all data created equal? Join our guests, Sarah Messou-Ghelazzi, Communications Officer, Filsan Hujaleh, Analyst with the Centre for Social Data Insights and Innovation, and Jeff Latimer, Director General - Accountable for Health, Justice, Diversity and Populations at Statistics Canada as we explore the role data can play to make Canada a more equal society for all.

    Release date: 2022-03-16
  • 4. Statistics 101: Exploring measures of central tendency Archived
    Stats in brief: 89-20-00062020002
    Description:

    This video is intended to teach viewers the differences between three fundamental statistical concepts. First, the mean, then the median and finally, the mode.

    Release date: 2021-05-03
  • 5. Statistics 101: Exploring measures of dispersion Archived
    Stats in brief: 89-20-00062020003
    Description:

    In this module, we will explore the concept of dispersion, also called variability. This concept includes: the range, the interquartile range, the standard deviation and the normal distribution.

    Release date: 2021-05-03
  • 6. Study: Measuring proximity to services and amenities Archived
    Stats in brief: 11-001-X202104628783
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2021-02-15
  • 7. Statistical standards: A national research and development standard Archived
    Stats in brief: 11-627-M2020072
    Description:

    This infographic provides an overview of the Canadian Research and Development Classification (CRDC), a national standard jointly developed by the Canada Foundation for Innovation (CFI), the Canadian Institutes of Health Research (CIHR), the Natural Sciences and Engineering Research Council of Canada (NSERC), the Social Sciences and Humanities Research Council of Canada (SSHRC), and Statistics Canada.

    Release date: 2020-10-05
  • 8. What is Data? An Introduction to Data Terminology and Concepts Archived
    Stats in brief: 89-20-00062020006
    Description:

    The data terminology and concepts covered in this video are datasets, databases, data protection, data variables, micro and macro data, and statistical information.

    Release date: 2020-09-23
  • 9. The Data Journey: What you need to know for successful navigation Archived
    Stats in brief: 89-20-00062020007
    Description:

    In this video you will learn about the steps and activities in the data journey, as well as the foundation supporting it.

    Release date: 2020-09-23
  • 10. Data stewardship: An introduction Archived
    Stats in brief: 89-20-00062020013
    Description:

    This video is intended for learners who wish to get a basic understanding of data stewardship. No previous knowledge is required.

    By the end of this video, you will be able to answer the following questions: What is data stewardship? What is the difference between data governance and data stewardship? Why is data stewardship important? What are the main roles of data stewards? What are the expected outcomes of a data stewardship program?

    Release date: 2020-09-23
Articles and reports (79)

Articles and reports (79) (0 to 10 of 79 results)

  • 1. Heterogeneous causal effects of labour market programs: A machine learning approach Archived
    Articles and reports: 11-522-X202200100017
    Description: In this paper, we look for presence of heterogeneity in conducting impact evaluations of the Skills Development intervention delivered under the Labour Market Development Agreements. We use linked longitudinal administrative data covering a sample of Skills Development participants from 2010 to 2017. We apply a causal machine-learning estimator as in Lechner (2019) to estimate the individualized program impacts at the finest aggregation level. These granular impacts reveal the distribution of net impacts facilitating further investigation as to what works for whom. The findings suggest statistically significant improvements in labour market outcomes for participants overall and for subgroups of policy interest.
    Release date: 2024-06-28
  • 2. A case study of using Splink: Census duplicate matching Archived
    Articles and reports: 11-522-X202200100002
    Description: The authors used the Splink probabilistic linkage package developed by the UK Ministry of Justice, to link census data from England and Wales to itself to find duplicate census responses. A large gold standard of confirmed census duplicates was available meaning that the results of the Splink implementation could be quality assured. This paper describes the implementation and features of Splink, gives details of the settings and parameters that we used to tune Splink for our particular project, and gives the results that we obtained.
    Release date: 2024-03-25
  • 3. Record linkage techniques to identify 2021 Canadian Census dwellings in the new Statistical Building Register Archived
    Articles and reports: 11-522-X202200100020
    Description: The reconciliation of 2021 census dwellings with the new Statistical Building Register (SBgR) presented linkage challenges. The Census of Population collected information from various dwelling types. For a large proportion of the population, mailing addresses were at the centre: they were used for reaching out to people and collected as contact info. In parallel, the register environment has been evolving. The agency is transitioning from the Address Register (AR) to the SBgR holding both mailing and location addresses, while also covering non-residential buildings. The reconciliation was conducted using a combination of systems, notably the new Register Matching Engine (RME) for difficult cases. The RME holds an interesting range of sophisticated string comparators. A deterministic linkage approach was used, while incorporating some data knowledge like the entropy. Through metadata, the matching expert could also reduce the amounts of false positives and false negatives.
    Release date: 2024-03-25
  • 4. Are “immortals” an issue for survival estimates derived from Canadian Cancer Registry data?
    Articles and reports: 82-003-X202301200002
    Description: The validity of survival estimates from cancer registry data depends, in part, on the identification of the deaths of deceased cancer patients. People whose deaths are missed seemingly live on forever and are informally referred to as “immortals”, and their presence in registry data can result in inflated survival estimates. This study assesses the issue of immortals in the Canadian Cancer Registry (CCR) using a recently proposed method that compares the survival of long-term survivors of cancers for which “statistical” cure has been reported with that of similar people from the general population.
    Release date: 2023-12-20
  • 5. Construction of a Northern Market Basket Measure of poverty for Nunavut
    Articles and reports: 75F0002M2022003
    Description: This discussion paper describes the proposed methodology for a Northern Market Basket Measure (MBM-N) for Nunavut, as well as identifies research which could be conducted in preparation for the 2023 review. The paper presents initial MBM-N thresholds and provides preliminary poverty estimates for reference years 2018 to 2021. A review period will follow the release of this paper, during which time Statistics Canada and Employment and Social Development Canada will welcome feedback from interested parties and work with experts, stakeholders, indigenous organizations, federal, provincial and territorial officials to validate the results.
    Release date: 2023-06-21
  • 6. Technical paper for the Northern Market Basket Measure of poverty for Yukon and the Northwest Territories
    Articles and reports: 75F0002M2022004
    Description:

    This technical paper describes the results of the review period, including small adjustments to the disposable income amounts used in the discussion paper Construction of a Northern Market Basket Measure (MBM-N) of poverty for Yukon and the Northwest Territories. It also marks the end of the review period for the MBM-N for Yukon and the Northwest Territories by presenting the latest poverty estimates for reference year 2020.

    Release date: 2022-11-03
  • 7. The System of National Quality-Of-Life Statistics: Conceptual Framework
    Articles and reports: 11-633-X2022002
    Description:

    This paper provides a description of the conceptual framework of the modernized system of national quality-of-life statistics that Statistics Canada is planning to implement within the next 5 to 10 years. Consistent with 50 years of dialogue on the improvement of social statistics, the conceptual framework proposes the adoption of a micro-level approach to describe how society operates and help create a cohesive and integrated system of quality-of-life statistics.

    Release date: 2022-06-01
  • 8. The System of National Quality-of-life Statistics: Future Directions
    Articles and reports: 11-633-X2021006
    Description:

    This paper describes the current thinking at Statistics Canada about future directions in social statistics. It describes how the system of statistics on social statistics (which would be renamed quality of life statistics) will look like in the next 5 to 10 years if Statistics Canada adopts the transformative methodologies and dissemination products that are needed to meet the growing demand for more disaggregated, timely, granular, accessible and more responsive statistics on quality of life.

    Release date: 2022-01-31
  • 9. Measuring Social Capital at the Neighbourhood Level: Experimental Estimates of Sense of Belonging to the Local Community Measured at the Census Tract Level
    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
  • 10. Construction of a Northern Market Basket Measure of poverty for Yukon and the Northwest Territories
    Articles and reports: 75F0002M2021007
    Description:

    This discussion paper describes the proposed methodology for a Northern Market Basket Measure (MBM-N) for Yukon and the Northwest Territories, as well as identifies research which could be conducted in preparation for the 2023 review. The paper presents initial MBM-N thresholds and provides preliminary poverty estimates for reference years 2018 and 2019. A review period will follow the release of this paper, during which time Statistics Canada and Employment and Social Development Canada will welcome feedback from interested parties and work with experts, stakeholders, indigenous organizations, federal, provincial and territorial officials to validate the results.

    Release date: 2021-11-12
Journals and periodicals (8)

Journals and periodicals (8) ((8 results))

  • 1. Statistics Canada International Symposium Series: Proceedings
    Journals and periodicals: 11-522-X
    Description: Since 1984, an annual international symposium on methodological issues has been sponsored by Statistics Canada. Proceedings have been available since 1987.
    Release date: 2024-06-28
  • 2. Survey Methodology
    Journals and periodicals: 12-001-X
    Geography: Canada
    Description: The journal publishes articles dealing with various aspects of statistical development relevant to a statistical agency, such as design issues in the context of practical constraints, use of different data sources and collection techniques, total survey error, survey evaluation, research in survey methodology, time series analysis, seasonal adjustment, demographic studies, data integration, estimation and data analysis methods, and general survey systems development. The emphasis is placed on the development and evaluation of specific methodologies as applied to data collection or the data themselves.
    Release date: 2024-06-25
  • 3. Statistical Methodology Research and Development Program Achievements
    Journals and periodicals: 12-206-X
    Description: This report summarizes the annual achievements of the Methodology Research and Development Program (MRDP) sponsored by the Modern Statistical Methods and Data Science Branch at Statistics Canada. This program covers research and development activities in statistical methods with potentially broad application in the agency’s statistical programs; these activities would otherwise be less likely to be carried out during the provision of regular methodology services to those programs. The MRDP also includes activities that provide support in the application of past successful developments in order to promote the use of the results of research and development work. Selected prospective research activities are also presented.
    Release date: 2023-10-11
  • 4. Geography Working Paper Series
    Journals and periodicals: 92F0138M
    Description:

    The Geography working paper series is intended to stimulate discussion on a variety of topics covering conceptual, methodological or technical work to support the development and dissemination of the division's data, products and services. Readers of the series are encouraged to contact the Geography Division with comments and suggestions.

    Release date: 2019-11-13
  • 5. Compendium of Management Practices for Statistical Organizations from Statistics Canada's International Statistical Fellowship Program
    Journals and periodicals: 11-634-X
    Description:

    This publication is a catalogue of strategies and mechanisms that a statistical organization should consider adopting, according to its particular context. This compendium is based on lessons learned and best practices of leadership and management of statistical agencies within the scope of Statistics Canada’s International Statistical Fellowship Program (ISFP). It contains four broad sections including, characteristics of an effective national statistical system; core management practices; improving, modernizing and finding efficiencies; and, strategies to better inform and engage key stakeholders.

    Release date: 2016-07-06
  • 6. Business Special Surveys and Technology Statistics Division Working Papers
    Journals and periodicals: 88F0006X
    Geography: Canada
    Description:

    Statistics Canada is engaged in the "Information System for Science and Technology Project" to develop useful indicators of activity and a framework to tie them together into a coherent picture of science and technology (S&T) in Canada. The working papers series is used to publish results of the different initiatives conducted within this project. The data are related to the activities, linkages and outcomes of S&T. Several key areas are covered such as: innovation, technology diffusion, human resources in S&T and interrelations between different actors involved in S&T. This series also presents data tabulations taken from regular surveys on research and development (R&D) and S&T and made possible by the project.

    Release date: 2011-12-23
  • 7. Survey Methods and Practices
    Journals and periodicals: 12-587-X
    Description:

    This publication shows readers how to design and conduct a census or sample survey. It explains basic survey concepts and provides information on how to create efficient and high quality surveys. It is aimed at those involved in planning, conducting or managing a survey and at students of survey design courses.

    This book contains the following information:

    -how to plan and manage a survey;-how to formulate the survey objectives and design a questionnaire; -things to consider when determining a sample design (choosing between a sample or a census, defining the survey population, choosing a survey frame, identifying possible sources of survey error); -choosing a method of collection (self-enumeration, personal interviews or telephone interviews; computer-assisted versus paper-based questionnaires); -organizing and conducting data collection operations;-determining the sample size, allocating the sample across strata and selecting the sample; -methods of point estimation and variance estimation, and data analysis; -the use of administrative data, particularly during the design and estimation phases-how to process the data (which consists of all data handling activities between collection and estimation) and use quality control and quality assurance measures to minimize and control errors during various survey steps; and-disclosure control and data dissemination.

    This publication also includes a case study that illustrates the steps in developing a household survey, using the methods and principles presented in the book. This publication was previously only available in print format and originally published in 2003.

    Release date: 2010-09-27
  • 8. Science and Technology Activities and Impacts: A Framework for a Statistical Information Archived
    Journals and periodicals: 88-522-X
    Description:

    The framework described here is intended as a basic operational instrument for systematic development of statistical information respecting the evolution of science and technology and its interactions with the society, the economy and the political system of which it is a part.

    Release date: 1999-02-24
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