Other content related to Statistical methods

Skip to filters. View results.

Results

All (166)

All (166) (20 to 30 of 166 results)

21. 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
22. 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
23. Integrating Machine Learning into Coding of the 2021 Canadian Census Using fastText Archived
Articles and reports: 11-522-X202100100010
Description:
As part of processing for the 2021 Canadian Census, the write-in responses to 31 census questions must be coded. Up until, and including, 2016, this was a three stage process, including an “interactive (human) coding” step as the second stage. This human coding step is both lengthy and expensive, spanning many months and requiring the hiring and training of a large number of temporary employees. With this in mind, for 2021, this stage was either augmented with or replaced entirely by machine learning models using the "fastText" algorithm. This presentation will discuss the implementation of this algorithm and the challenges and decisions taken along the way.

Key Words: Natural Language Processing, Machine Learning, fastText, Coding

Release date: 2021-11-05
24. Statistics Netherlands and AI Archived
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
25. Machine Learning Classifier Evaluation Criteria: application to price statistics Archived
Articles and reports: 11-522-X202100100012
Description: The modernization of price statistics by National Statistical Offices (NSO) such as Statistics Canada focuses on the adoption of alternative data sources that include the near-universe of all products sold in the country, a scale that requires machine learning classification of the data. The process of evaluating classifiers to select appropriate ones for production, as well as monitoring classifiers once in production, needs to be based on robust metrics to measure misclassification. As commonly utilized metrics, such as the Fß-score may not take into account key aspects applicable to prices statistics in all cases, such as unequal importance of categories, a careful consideration of the metric space is necessary to select appropriate methods to evaluate classifiers. This working paper provides insight on the metric space applicable to price statistics and proposes an operational framework to evaluate and monitor classifiers, focusing specifically on the needs of the Canadian Consumer Prices Index and demonstrating discussed metrics using a publicly available dataset.

Key Words: Consumer price index; supervised classification; evaluation metrics; taxonomy
Release date: 2021-11-05
26. Need for Speed: Using fastText (Machine Learning) to Code the Labour Force Survey Archived
Articles and reports: 11-522-X202100100013
Description: Statistics Canada’s Labour Force Survey (LFS) plays a fundamental role in the mandate of Statistics Canada. The labour market information provided by the LFS is among the most timely and important measures of the Canadian economy’s overall performance. An integral part of the LFS monthly data processing is the coding of respondent’s industry according to the North American Industrial Classification System (NAICS), occupation according to the National Occupational Classification System (NOC) and the Primary Class of Workers (PCOW). Each month, up to 20,000 records are coded manually. In 2020, Statistics Canada worked on developing Machine Learning models using fastText to code responses to the LFS questionnaire according to the three classifications mentioned previously. This article will provide an overview on the methodology developed and results obtained from a potential application of the use of fastText into the LFS coding process.
Key Words: Machine Learning; Labour Force Survey; Text classification; fastText.
Release date: 2021-11-05
27. 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
28. 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
29. 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
30. 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

Data (1)

Data (1) ((1 result))

1. 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 (105)

Analysis (105) (50 to 60 of 105 results)

51. Business statistics: A new approach Archived
Stats in brief: 11-001-X201516812543
Description: Release published in The Daily – Statistics Canada’s official release bulletin
Release date: 2015-06-17
52. Canadian Health Measures Survey: A tool for immigrant health research? Archived
Articles and reports: 82-003-X201500314143
Description:
This study evaluates the representativeness of the pooled 2007/2009-2009/2011 Canadian Health Measures Survey immigrant sample by comparing it with socio-demographic distributions from the 2006 Census and the 2011 National Household Survey, and with selected self-reported health and health behaviour indicators from the 2009/2010 Canadian Community Health Survey.
Release date: 2015-03-18
53. Researcher’s Blog Archived
Stats in brief: 11-001-X201503410941
Description: Release published in The Daily – Statistics Canada’s official release bulletin
Release date: 2015-02-03
54. Sampling and Weighting Technical Report: National Household Survey 2011 Archived
Stats in brief: 11-001-X201502811581
Description: Release published in The Daily – Statistics Canada’s official release bulletin
Release date: 2015-01-28
55. On aligned composite estimates from overlapping samples for growth rates and totals Archived
Articles and reports: 12-001-X201400214097
Description:
When monthly business surveys are not completely overlapping, there are two different estimators for the monthly growth rate of the turnover: (i) one that is based on the monthly estimated population totals and (ii) one that is purely based on enterprises observed on both occasions in the overlap of the corresponding surveys. The resulting estimates and variances might be quite different. This paper proposes an optimal composite estimator for the growth rate as well as the population totals.
Release date: 2014-12-19
56. Bayes linear estimation for finite population with emphasis on categorical data Archived
Articles and reports: 12-001-X201400111886
Description:
Bayes linear estimator for finite population is obtained from a two-stage regression model, specified only by the means and variances of some model parameters associated with each stage of the hierarchy. Many common design-based estimators found in the literature can be obtained as particular cases. A new ratio estimator is also proposed for the practical situation in which auxiliary information is available. The same Bayes linear approach is proposed for obtaining estimation of proportions for multiple categorical data associated with finite population units, which is the main contribution of this work. A numerical example is provided to illustrate it.
Release date: 2014-06-27
57. National Saving in Canada and the United States, 1926 to 2011 Archived
Articles and reports: 11F0027M2014093
Geography: Canada
Description:
This paper examines the composition of Canadian and United States gross national saving for a period spanning more than 80 years, using time series from the Bureau of Economic Analysis in the United States and a newly created dataset for Canada. The paper tracks short-term, year-to-year fluctuations, cyclical fluctuations and long-term compositional changes. It illustrates a substantial degree of national saving reallocation across sectors, annually and across business cycles. The national saving rate is more stable than sector saving rates, implying that sectoral changes have been largely offsetting.
Release date: 2014-06-26
58. Data Inventory Project 2012 Archived
Stats in brief: 11-001-X20131127661
Description: Release published in The Daily – Statistics Canada’s official release bulletin
Release date: 2013-04-22
59. Evaluation of the Canadian Household Panel Survey Pilot Content Archived
Articles and reports: 89-648-X2013001
Geography: Canada
Description:
In the fall of 2008, Statistics Canada, in partnership with Human Resources and Social Development Canada (HRSDC) and the Canadian academic community, put into the field the Canadian Household Panel Survey Pilot (CHPS-Pilot). This paper describes the background of the project, the steps taken in the development of the pilot survey, and the results of a series of explorations of the data collected.
Release date: 2013-01-24
60. 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

Reference (55)

Reference (55) (0 to 10 of 55 results)

1. Concepts and Methods Guide for the Indigenous Peoples Survey and Indigenous Peoples Survey – Nunavut Inuit Supplement, 2022
Surveys and statistical programs – Documentation: 89-653-X2024002
Description: This guide is intended to provide a detailed review of both the 2022 IPS and IPS–NIS with respect to subject matter and methodological approaches. It is designed to help data users by serving as a guide to the concepts and measures of the survey as well as the technical details of the survey’s design, field work and data processing. This guide is meant to provide users with helpful information on how to use and interpret survey results. The discussion on data quality also allows users to review the strengths and limitations of the data for their particular needs.
Chapter 1 of this guide provides an overview of the 2022 IPS and IPS–NIS by introducing the survey background and objectives. Chapter 2 outlines the survey’s themes and explains the key concepts and definitions used for the survey. Chapters 3 to 6 cover important aspects of the survey methodology, sampling design, data collection and processing. Chapters 7 and 8 review issues of data quality and caution users about comparing 2022 IPS or IPS–NIS data with data from other sources. Chapter 9 outlines the survey products available to the public, including data tables, analytical articles and reference material. The appendices provide a comprehensive list of survey indicators, extra coding categories and standard classifications used on both the IPS and the IPS–NIS. Lastly, a glossary of survey terms and information on confidence intervals is also provided.
Release date: 2024-08-14
2. Guide to the Job Vacancy and Wage Survey
Surveys and statistical programs – Documentation: 75-514-G
Description: The Guide to the Job Vacancy and Wage Survey contains a dictionary of concepts and definitions, and covers topics such as survey methodology, data collection, processing, and data quality. The guide covers both components of the survey: the job vacancy component, which is quarterly, and the wage component, which is annual.
Release date: 2024-06-18
3. 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
4. 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
5. Statistics Canada Data Strategy
Surveys and statistical programs – Documentation: 89-26-0003
Description:
Statistics Canada Data Strategy (SCDS) provides a course of action for managing and leveraging the agency’s data assets to ensure their optimal use and value while maintaining public trust. As Statistics Canada is the nation’s trusted provider of high-quality data and information to support evidence-based policy and decision making, the SCDS also naturally includes the agency’s plan for providing support and data expertise to other government organizations (federal, provincial and territorial), non-governmental organizations, the private sector, academia, and other national and international communities).
The SCDS provides a roadmap for how Statistics Canada will continue to govern and manage its valuable data assets as part of its modernization agenda and in alignment with and response to other federal government strategies and initiatives. These federal strategies include the Data Strategy for the Federal Public Service, Canada’s 2018-2020 National Action Plan on Open Government, and the Treasury Board Secretariat Digital Operations Strategic Plan: 2018-2022.
Release date: 2020-04-30
6. National Household Survey: Aboriginal Peoples
Surveys and statistical programs – Documentation: 99-011-X
Description:
This topic presents data on the Aboriginal peoples of Canada and their demographic characteristics. Depending on the application, estimates using any of the following concepts may be appropriate for the Aboriginal population: (1) Aboriginal identity, (2) Aboriginal ancestry, (3) Registered or Treaty Indian status and (4) Membership in a First Nation or Indian band. Data from the 2011 National Household Survey are available for the geographical locations where these populations reside, including 'on reserve' census subdivisions and Inuit communities of Inuit Nunangat as well as other geographic areas such as the national (Canada), provincial and territorial levels.
Analytical products
The analytical document provides analysis on the key findings and trends in the data, and is complimented with the short articles found in NHS in Brief and the NHS Focus on Geography Series.
Data products
The NHS Profile is one data product that provides a statistical overview of user selected geographic areas based on several detailed variables and/or groups of variables. Other data products include data tables which represent a series of cross tabulations ranging in complexity and are available for various levels of geography.
Release date: 2019-10-29
7. Classifying Cannabis in the Canadian Statistical System Archived
Surveys and statistical programs – Documentation: 11-621-M2018105
Description:
Statistics Canada needs to respond to the legalization of cannabis for non-medical use by measuring various aspects of the introduction of cannabis in the Canadian economy and society. An important part of measuring the economy and society is using statistical classifications. It is common practice with classifications that they are updated and revised as new industries, products, occupations and educational programs are introduced into the Canadian economy and society. This paper describes the changes to the various statistical classifications used by Statistics Canada in order to measure the introduction of legal non-medical cannabis.
Release date: 2019-07-24
8. Analytical Studies Branch Annual Consolidated Plan for Research, Data Development and Modelling, 2019/2020 Archived
Surveys and statistical programs – Documentation: 11-633-X2019001
Description:
The mandate of the Analytical Studies Branch (ASB) is 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 large range of statistical sources to describe, draw inferences from, and make objective and scientifically supported deductions about the evolving nature of the Canadian economy and society. Research questions are addressed by applying leading-edge methods, including microsimulation and predictive analytics using a range of linked and integrated administrative and survey data. In supporting greater access to data, ASB linked data are made available to external researchers and policy makers to support evidence-based decision making. Research results are disseminated by the branch using a range of mediums (i.e., research papers, studies, infographics, videos, and blogs) to meet user needs. The branch also provides analytical support and training, feedback, and quality assurance to the wide range of programs within and outside Statistics Canada.
Release date: 2019-05-29
9. Transition of Labour Force Survey Data Processing to the Social Survey Processing Environment (SSPE) Archived
Surveys and statistical programs – Documentation: 75-005-M2019001
Description:
The production of statistics from the Labour Force Survey (LFS) involves many activities, one of which is data processing. This step involves the verification and correction of survey data when required in order to produce microdata files. Beginning in January 2019, LFS processing will be transitioned to a new system, the Social Survey Processing Environment. This document describes the development and testing that preceded the implementation of the new system, and demonstrates that the transition is expected to have minimal impact on LFS estimates and be transparent to users of LFS data.
Release date: 2019-02-08
10. Methodology of the Canadian Labour Force Survey
Surveys and statistical programs – Documentation: 71-526-X
Description:
The Canadian Labour Force Survey (LFS) is the official source of monthly estimates of total employment and unemployment. Following the 2011 census, the LFS underwent a sample redesign to account for the evolution of the population and labour market characteristics, to adjust to changes in the information needs and to update the geographical information used to carry out the survey. The redesign program following the 2011 census culminated with the introduction of a new sample at the beginning of 2015. This report is a reference on the methodological aspects of the LFS, covering stratification, sampling, collection, processing, weighting, estimation, variance estimation and data quality.
Release date: 2017-12-21

Report a problem or mistake on this page

Date modified:: 2024-09-19

Other content related to Statistical methods

Filter results by

Keyword(s)

Type

Geography

Survey or statistical program

Content

Results

All (166) (20 to 30 of 166 results)

Data (1) ((1 result))

Analysis (105) (50 to 60 of 105 results)

Reference (55) (0 to 10 of 55 results)

Other content related to Statistical methods

Filter results by

Keyword(s)

Type

Geography

Survey or statistical program

Content

Results

All (166) (20 to 30 of 166 results)

Data (1) ((1 result))

Analysis (105) (50 to 60 of 105 results)

Reference (55) (0 to 10 of 55 results)

How do I use the filters and the search box?

How do I refine my search?

How does the search work?

How are the results ordered?

How are the results ordered?