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41. Supervised Text Classification with Leveled Homomorphic Encryption Archived
Articles and reports: 11-522-X202100100027
Description:
Privacy concerns are a barrier to applying remote analytics, including machine learning, on sensitive data via the cloud. In this work, we use a leveled fully Homomorphic Encryption scheme to train an end-to-end supervised machine learning algorithm to classify texts while protecting the privacy of the input data points. We train our single-layer neural network on a large simulated dataset, providing a practical solution to a real-world multi-class text classification task. To improve both accuracy and training time, we train an ensemble of such classifiers in parallel using ciphertext packing.

Key Words: Privacy Preservation, Machine Learning, Encryption

Release date: 2021-10-29
42. Statistical Disclosure Control and Developments in Formal Privacy: In Memoriam to Chris Skinner Archived
Articles and reports: 11-522-X202100100022
Description:
I provide an overview of the evolution of Statistical Disclosure Control (SDC) research over the last decades and how it has evolved to handle the data revolution with more formal definitions of privacy. I emphasize the many contributions by Chris Skinner in the research areas of SDC. I will review his seminal research, starting in the 1990’s with his work on the release of UK Census sample microdata. This led to a wide-range of research on measuring the risk of re-identification in survey microdata through probabilistic models. I also focus on other aspects of Chris’ research in SDC. Chris was the recipient of the 2019 Waksberg Award and sadly never got a chance to present his Waksberg Lecture at the Statistics Canada International Methodology Symposium. This paper follows the outline that Chris had prepared in preparation for that lecture, and provided to me by his son, Tom Skinner. Keywords: Risk of Re-identification, Data Revolution, Privacy Models, Differential Privacy

Release date: 2021-10-22
43. Random Forest models, a proposal for the analysis of selective editing strategies Archived
Articles and reports: 11-522-X202100100021
Description: Istat has started a new project for the Short Term statistical processes, to satisfy the coming new EU Regulation to release estimates in a shorter time. The assessment and analysis of the current Short Term Survey on Turnover in Services (FAS) survey process, aims at identifying how the best features of the current methods and practices can be exploited to design a more “efficient” process. In particular, the project is expected to release methods that would allow important economies of scale, scope and knowledge to be applied in general to the STS productive context, usually working with a limited number of resources. The analysis of the AS-IS process revealed that the FAS survey incurs substantial E&I costs, especially due to intensive follow-up and interactive editing that is used for every type of detected errors. In this view, we tried to exploit the lessons learned by participating to the High-Level Group for the Modernisation of Official Statistics (HLG-MOS, UNECE) about the Use of Machine Learning in Official Statistics. In this work, we present a first experiment using Random Forest models to: (i) predict which units represent “suspicious” data, (ii) to assess the prediction potential use over new data and (iii) to explore data to identify hidden rules and patterns. In particular, we focus on the use of Random Forest modelling to compare some alternative methods in terms of error prediction efficiency and to address the major aspects for the new design of the E&I scheme.
Release date: 2021-10-15
44. Sample empirical likelihood approach under complex survey design with scrambled responses
Articles and reports: 12-001-X202100100003
Description:
One effective way to conduct statistical disclosure control is to use scrambled responses. Scrambled responses can be generated by using a controlled random device. In this paper, we propose using the sample empirical likelihood approach to conduct statistical inference under complex survey design with scrambled responses. Specifically, we propose using a Wilk-type confidence interval for statistical inference. Our proposed method can be used as a general tool for inference with confidential public use survey data files. Asymptotic properties are derived, and the limited simulation study verifies the validity of theory. We further apply the proposed method to some real applications.
Release date: 2021-06-24
45. Demystifying Confidence Intervals
19-22-0005
Description:
In this session, we will attempt to demystify the concept of confidence intervals as they relate to sample data. A practical approach is used, placing emphasis on the meaning and interpretation of results rather than the mathematics. The goal is to make sense of some common challenges faced by data users when interpreting confidence intervals. The session is intended for a beginner audience. Some familiarity with basic statistical concepts would be beneficial/advantageous but not required.
https://www.statcan.gc.ca/eng/wtc/information/19220005
Release date: 2021-05-28
46. Statistics 101: Correlation and Causality Archived
Stats in brief: 89-20-00062021002
Description:
This video is intended for viewers who wish to gain a basic understanding of correlation and causality. As a prerequisite, before beginning this video, we highly recommend having already completed our videos titled “What is Data? An Introduction to Data Terminology and Concepts” and “Types of Data: Understanding and Exploring Data”.
Release date: 2021-05-03
47. Statistics Canada British Columbia Opioid Overdose Analytical File: Technical Report
Articles and reports: 11-633-X2021003
Description:
Canada continues to experience an opioid crisis. While there is solid information on the demographic and geographic characteristics of people experiencing fatal and non-fatal opioid overdoses in Canada, there is limited information on the social and economic conditions of those who experience these events. To fill this information gap, Statistics Canada collaborated with existing partnerships in British Columbia, including the BC Coroners Service, BC Stats, the BC Centre for Disease Control and the British Columbia Ministry of Health, to create the Statistics Canada British Columbia Opioid Overdose Analytical File (BC-OOAF).
Release date: 2021-02-17
48. Construction and Assessment of a Social Inclusion Index for the Canada Mortgage and Housing Corporation: Technical Report
Articles and reports: 11-633-X2021001
Description:
Using data from the Canadian Housing Survey, this project aimed to construct a measure of social inclusion, using indicators identified by the Canada Mortgage and Housing Corporation (CMHC), to report a social inclusion score for each geographic stratum separately for dwellings that are and are not in social and affordable housing. This project also sought to examine associations between social inclusion and a set of economic, social and health variables.
Release date: 2021-01-05
49. Firth’s penalized likelihood for proportional hazards regressions for complex surveys
Articles and reports: 12-001-X202000200004
Description:
This article proposes a weight scaling method for Firth’s penalized likelihood for proportional hazards regression models. The method derives a relationship between the penalized likelihood that uses scaled weights and the penalized likelihood that uses unscaled weights, and it shows that the penalized likelihood that uses scaled weights have some desirable properties. A simulation study indicates that the penalized likelihood using scaled weights produces smaller biases in point estimates and standard errors than the biases produced by the penalized likelihood using unscaled weights. The weighted penalized likelihood is applied to estimate hazard rates for heart attacks by using a public-use data set from the National Health and Epidemiology Followup Study (NHEFS). SAS® statements to estimate hazard rates using data from complex surveys are given in the appendix.
Release date: 2020-12-15
50. How to Build a Robots! Database
Articles and reports: 11-633-X2020004
Description:
Recent advances in artificial intelligence have rekindled ancient fears that robots will replace humans in the economy. Previous waves of automation changed but did not reduce labour’s role, but robots’ human-like flexibility could make this time different. Whether or not it will is an empirical question that has lacked suitable data to answer. This paper describes the creation of a dataset to fill the evidence gap in Canada. Robots! is firm-level panel data on robot adoption created using Canadian import data. The data identify a substantial amount of the robot investment in the Canadian economy from 1996 to 2017. Although many robots are imported by robotics wholesalers or programmers for resale, the majority of them can be attributed to their final (direct) adopting firm. The data can be used to study the impact of robot adoption at the economic region, industry or firm-level.
Release date: 2020-11-02

Data (2)

Data (2) ((2 results))

1. Canadian Statistical Geospatial Explorer Hub
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
2. 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

Analysis (246)

Analysis (246) (20 to 30 of 246 results)

21. Sustainable Development Goals: Goal 1, No Poverty
Articles and reports: 11-637-X202200100001
Description:
As the first goal outlined in the 2030 Agenda for Sustainable Development, Canada and other UN member states have committed to end poverty in all its forms everywhere by 2030. This 2022 infographic provides an overview of indicators underlying the first Sustainable Development Goal in support of eradicating poverty, and the statistics and data sources used to monitor and report on this goal in Canada.

Release date: 2022-06-23
22. Sustainable Development Goals: Goal 2, Zero Hunger
Articles and reports: 11-637-X202200100002
Description:
As the second goal outlined in the 2030 Agenda for Sustainable Development, Canada and other UN member states have committed to end hunger, achieve food security and improved nutrition, and promote sustainable agriculture by 2030. This 2022 infographic provides an overview of indicators underlying the second Sustainable Development Goal in support of ending hunger, and the statistics and data sources used to monitor and report on this goal in Canada.

Release date: 2022-06-23
23. Sustainable Development Goals: Goal 3, Good Health and Well-being
Articles and reports: 11-637-X202200100003
Description:
As the third goal outlined in the 2030 Agenda for Sustainable Development, Canada and other UN member states have committed to ensure healthy lives and promote well-being for all at all ages by 2030. This 2022 infographic provides an overview of indicators underlying the third Sustainable Development Goal in support of Good Health and Well-being, and the statistics and data sources used to monitor and report on this goal in Canada.

Release date: 2022-06-23
24. Confidentiality Vetting Support: Dominance and homogeneity using SAS Archived
Stats in brief: 89-20-00082021001
Description: This video is part of the confidentiality vetting support series and presents examples of how to use SAS to perform the dominance and homogeneity test while using the Census.
Release date: 2022-04-29
25. Confidentiality Vetting Support: Proportion and round tool using SAS Archived
Stats in brief: 89-20-00082021002
Description: This video is part of the confidentiality vetting support series and presents examples of how to use SAS to create proportion output for researchers working with confidential data.
Release date: 2022-04-27
26. Confidentiality Vetting Support: Rounding proportions using Stata Archived
Stats in brief: 89-20-00082021003
Description: This video is part of the confidentiality vetting support series and presents examples of how to use Stata to create proportion output for researchers working with confidential data.
Release date: 2022-04-27
27. Confidentiality Vetting Support: Dominance and homogeneity using the tcensus function (Stata) Archived
Stats in brief: 89-20-00082021004
Description: This video is part of the confidentiality vetting support series and presents examples of how to use Stata to perform the dominance and homogeneity test while using the Census.
Release date: 2022-04-27
28. Confidentiality Vetting Support: Rounding proportions using Rounder An R Shiny App Archived
Stats in brief: 89-20-00082021005
Description: This video is part of the confidentiality vetting support series and presents examples of how to use R to create proportion output for researchers working with confidential data.
Release date: 2022-04-27
29. Confidentiality Vetting Support: Dominance and homogeneity using R Archived
Stats in brief: 89-20-00082021006
Description: This video is part of the confidentiality vetting support series and presents examples of how to use R to perform the dominance and homogeneity test while using the Census.
Release date: 2022-04-27
30. The Journey of Statistics Canada Data: Why it Matters to You Archived
Stats in brief: 11-627-M2022016
Description:
This infographic explains the steps involved in collecting data for all Statistics Canada household and business surveys. The responses are compiled, analyzed and used to make important decisions and are kept strictly confidential.

Release date: 2022-02-28

Reference (22)

Reference (22) (0 to 10 of 22 results)

1. 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
2. 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
3. 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
4. Painting a Portrait of Canada: The 2021 Census of Population
Notices and consultations: 98-26-0001
Description:
This white paper presents Statistics Canada’s planned approach to the 2021 Census of Population and provides a clear explanation of the processes behind the census program, touching on historical, legal, operational and content aspects. Statistics Canada recognizes that it is important to not only successfully conduct the census, but also to be transparent and informative about the way in which those efforts are accomplished. Painting a Portrait of Canada: The 2021 Census of Population gives readers an exclusive, detailed look at how census data is collected, analyzed and given back to Canadians, in the form of high-quality statistical information, used to make evidence-based decisions in Canadian society.
Release date: 2020-07-20
5. Using family-related variables from the Census of Population and the National Household Survey microdata files Archived
Surveys and statistical programs – Documentation: 91F0015M2016012
Description:
This article provides information on using family-related variables from the microdata files of Canada’s Census of Population. These files exist internally at Statistics Canada, in the Research Data Centres (RDCs), and as public-use microdata files (PUMFs). This article explains certain technical aspects of all three versions, including the creation of multi-level variables for analytical purposes.
Release date: 2016-12-22
6. The Data Warehouse and analytical tools to facilitate the integration of the Canadian Macroeconomic Accounts Archived
Surveys and statistical programs – Documentation: 11-522-X201700014710
Description:
The Data Warehouse has modernized the way the Canadian System of Macroeconomic Accounts (MEA) are produced and analyzed today. Its continuing evolution facilitates the amounts and types of analytical work that is done within the MEA. It brings in the needed element of harmonization and confrontation as the macroeconomic accounts move toward full integration. The improvements in quality, transparency, and timeliness have strengthened the statistics that are being disseminated.
Release date: 2016-03-24
7. Note to Users of Data from the 2012 Canadian Income Survey
Notices and consultations: 75-513-X2014001
Description:
Starting with the 2012 reference year, annual individual and family income data is produced by the Canadian Income Survey (CIS). The CIS is a cross-sectional survey developed to provide information on the income and income sources of Canadians, along with their individual and household characteristics. The CIS reports on many of the same statistics as the Survey of Labour and Income Dynamics (SLID), which last reported on income for the 2011 reference year. This note describes the CIS methodology, as well as the main differences in survey objectives, methodology and questionnaires between CIS and SLID.
Release date: 2014-12-10
8. Using a Trend-cycle Approach to Estimate Changes in Southern Canada's Water Yield from 1971 to 2004 Archived
Surveys and statistical programs – Documentation: 16-001-M2010014
Description: Quantifying how Canada's water yield has changed over time is an important component of the water accounts maintained by Statistics Canada. This study evaluates the movement in the series of annual water yield estimates for Southern Canada from 1971 to 2004. We estimated the movement in the series using a trend-cycle approach and found that water yield for southern Canada has generally decreased over the period of observation.
Release date: 2010-09-13
9. Finding and Using Statistics Archived
Surveys and statistical programs – Documentation: 11-533-X
Description:
This guide has been created especially for users needing a step-by-step review on how to find, read and use data, with quick tips on locating information on the Statistics Canada website. Originally published in paper format in the 1980s, revised as part of the 1994 Statistics Canada Catalogue, and then transformed into an electronic version, this guide is continually being updated to maintain its currency and usefulness.
Release date: 2007-11-19
10. Trade in Culture Services A Handbook of Concepts and Methods Archived
Surveys and statistical programs – Documentation: 81-595-M2007056
Geography: Canada
Description:
This handbook discusses the collection and interpretation of statistical data on Canada's trade in culture services.
Release date: 2007-10-31

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