Statistics Canada's Covid-19: A Data Perspective is an excellent starting point for research on Covid-19. Links through to all relevant StatCan releases.
For more research and data related to the COVID-19 pandemic, see Dalhousie University Libraries' excellent COVID-19 Research and Information Sources. Most resources in the Dal guide will be publically accessible.
This guide provides starting points for finding statistics information and data sets. Some resources provided are limited to the use of the Saint Mary's University community. Other data sources listed here are open access and freely available online.
Talk to us! We can help you navigate various statistics and data tools, such as the Statistics Canada collections, industry and company performance data sources, and more . Drop by our Research Help Desk, or make an appointment to discuss your project and data requirements.
The Library participates in Statistics Canada's Data Liberation Initiative (DLI) and can provide access for research purposes to Public Use Microdata Files (PUMFs) from many of Statistics Canada survey programs. Researchers requiring access to StatCan PUMFs, databases and geographic files should contact the Library’s DLI representative, Joyce Thomson via Teams Call or email at firstname.lastname@example.org
The terms statistics and data are often used interchangeably. Although there are some commonly understood distinctions, there are also grey areas: statistics are a kind of data, and data are used to generate statistics. There are some distinctions between the two terms:
Statistics often are:
Data can generally be used to:
When thinking about using data, consider what type type of data you may need - microdata or aggregate data. Microdata is the original, (mostly) unprocessed information* such as the level of education attained by each member of a household, the height and species of each tree in a park. Aggregate data is summarized and combined in some way: average education levels in a city, number of oak trees in a city park.
*(microdata is processed a bit, to protect privacy of participants, but respondent answers remain substantially intact)
Content adapted with permission from Brock University Library
First things first: slow down. Don't focus on the numbers in the table right away. Instead, carefully review the details around the edges: what information is given by the title or header? What are the row and column labels? Are there any footnotes or references underneath the table? All of this information can help you understand the context of the numbers that are inside the table.
Questions to ask (and answer!) when looking at numerical data or statistics:
Many factors can affect what data is collected and why, and other factors affect what can be shared with others. A few common issues that arise with published data and statistics include (1) the need to protect privacy, 2. the effort to control for accuracy and precision, 3. mandated measurements (such as the census), and 4. pre-existing categories with which to organize the data.
Statistical Analysis Software:
Source: DLI Survival Guide
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