Research Guides: Data & Statistics: Getting Started

Welcome & Quick Links

This guide is meant to provide you with starting points for finding microdata, aggregate data, data analysis tools and more.

Need some help? As your Data Librarian, I am available to help answer any data, library or research-related questions you may have. Feel free to schedule an appointment with me using the 'Schedule Appointment' button under my photo.

Terminology

Data

Data are information or characteristics collected through observation, meaning there are many different types of data including:

Microdata

Microdata are the individual responses or observations, before statistical analysis has been applied. Sometimes referred to as "raw" data. Microdata usually needs to be interpreted using analysis software. Microdata collected about people needs to be anonymized before they can be published for public use so specific individuals cannot be identified.

Aggregate Data

Unlike microdata, aggregate data, or statistics, are not in their 'raw form'. They are the result of statistical analysis, often compiled and presented in a summary report or a table. Totals, averages, and percentages are examples of aggregate data.

Geospatial Data

Data that includes geographic positioning information relative to a coordinate system. Geospatial data usually needs to be interpreted using GIS software.

Time Series Data

Observations of the same variable made over time, such as climate data.

Textual Data

Systematically collected material consisting of written, printed, or electronically published words, typically either purposefully written or transcribed from speech.

News & Training

*NEW DATA BY TOPIC*: Systemic Racism & Police Brutality
Click to view new topic(s) added to the 'Data by Topic' tab on this guide.
Webinar (Recording): Writing an article with excellent supporting data
Recorded on June 22, 2020. Science requires evidence behind an assertion. As William Deming said, “without data, you’re just another person with an opinion.” So the argument in a research article must have some sort of evidence, i.e. data, behind it. But does the data support the article or does the article support the data? Both actually. It is the responsibility of the researcher to provide a package of evidence and argument in order to advance our understanding.

This presentation will introduce ways to interconnect your article and data in ways that make them most readily understood and useful by others. Topics include how to prepare data for presentation, how to ensure the data are well stewarded, and how to provide fair credit and access to data through citation. It will also touch briefly on other research outputs like software and protocols.
Webinar (Recording): Statistics Canada Research Data Centre (RDC) Alternatives
The Real Time Remote Access (RTRA) program offers one alternative way to access confidential Statistics Canada data. Other options include using the Statistics Canada public use files and analyzing data from other sources.

The presenters will discuss the differences between the data that can be accessed through the RTRA vs. the RDC. RTRA data is a very useful option for some types of questions but also has some important limitations. In addition, they will highlight alternative sources of data from the U.S. and elsewhere that are similar to the Statistics Canada master datasets.

Data & Statistics