Analysis 101: How to read a table

Catalogue number: 892000062023002

Release date: October 24, 2023

By the end of this video, you will have a better understanding of why data tables are important, how data tables are structured and how to interpret data quality indicators within a table.

Data journey step
Analyze, model
Data competencies
Data analysis, Data interpretation
Suggested prerequisites

Watch the video

Analysis 101: How to read a table - Transcript

(The Statistics Canada symbol and Canada wordmark appear on screen with the title: "Analysis 101: How to read a table".)

Analysis 101: How to read a table

Welcome to our video on how to read a data table.

If you want to learn how to read data tables quickly and efficiently, then you are in the right place.

Learning goals

(Text on screen: No prerequisite learning is required to fully understand this video.)

By the end of this video, you will have a better understanding of why data tables are important, how data tables are structured and how to interpret data quality indicators within a table.

This video is for learners beginning their own journey to increase their current level of data literacy. No prerequisite learning is required to fully understand this video.

Steps in the data journey

(Diagram of the Steps of the data journey: Step 1 - define, find, gather; Step 2 - explore, clean, describe; Step 3 - analyze, model; Step 4 - tell the story. The data journey is supported by a foundation of stewardship, metadata, standards and quality.)

This diagram is a visual representation of the data journey, from collecting the data; to exploring, cleaning, describing and understanding the data; to analyzing the data; and lastly to communicating with others the story the data tell.

Steps in the data journey

(Diagram of the Steps of the data journey with an emphasis on Step 3: Analyze and model.)

Knowing how to accurately interpret data from a table and transform it into useful information is part of the third step in the data journey, analyze and model.

What is a data table?

First, what is a data table? A data table is a structured arrangement of data in rows and columns. It's used to display a large amount of numerical information in an organized manner. It provides a clear and concise way to present and analyze data.

What are data tables used for?

Data tables are used to simplify complex data sets for easy understanding, to facilitate comparison and analysis of data points, to enable identification of trends, patterns, and outliers, and lastly to provide a foundation for creating charts, graphs, and visualizations.

How are data tables structured?

(Graph demonstrating the prevalence of disability for people aged 15 and over, by age group, Yukon, 2017.)

In the next few slides, we're going to look at the main parts of a table step by step, using a detailed example to illustrate the different components of a data table that help organize and display information. Such components include title, column headers, sources, notes, row stubs, cells, and data quality.

How to read a table

Did you know that Canadians with disabilities are twice as likely to live in poverty than those without disabilities? By addressing the longstanding inequities that lead to financial insecurity, hardships and social exclusion faced by persons with disabilities, in June of 2021, the Government of Canada committed to building a disability-inclusive Canada. Here we have an example of a data table that could play a small role in informing that decision. It shows the prevalence of disability for adults by age group in the Yukon in 2017.

Step 1: Look at the title

So how do you read this table? Step 1: look at the title. "Prevalence of disability for people aged 15 and over by age group, Yukon, 2017" tells us the proportion of the adult population, broken down by age group, in the Yukon, that experiences some form of disability at a given point in time.

Step 2: Identify the column headers

Here we have 4 columns titled "Age groups", "Total population", "Persons with disabilities" and "Prevalence of disability". The prevalence is expressed as a percentage and provides an indication of how common disabilities are within each specific age group. These headers tell us that the table shows data on the prevalence of disability, both in whole numbers and percentages, by age group, for the entire adult population of Yukon.

Step 3: Check the sources and notes

In our case, the source is "Statistics Canada, Canadian Survey on Disability 2017". This tells us that the data come from an official government source and therefore should be considered reliable. Checking the reliability of any data source is key to ensuring you are interpreting and analyzing trustworthy data. Do not trust a table that does not clearly show the source of the data.

Step 4: Identify the row stubs.

Here, the row stubs are the total number of survey participants aged 15 and over, and then subsequently, each row breaks that total down by age group. Note that the sum of the values for each category may differ from the total due to rounding. For example, in theory, if you add up the age group "15 to 64" and "75 and over" you should get the same number as the "Total - aged 15 and over", but as the note in the table reads, this is not always the case because the data are rounded for ease of use when the table is created.

Step 5: Examine the cells

To find the prevalence of disability for a specific age group, locate the row and column that you're interested in and find the cell where they intersect. For example, the prevalence of disability for those aged 45 to 64 is found in the cell where the "45 to 64" row and the "Prevalence of disability" column intersect, which shows a prevalence of 29.1%, which represents 3070 / 10,550, the number of persons with disabilities aged 45 to 64 divided by the total number of persons in that age group.

Step 6: Look for patterns or trends.

(In the graph, there is a superscript E beside a value.)

By examining the data, you might notice that as the groups progress in age, the prevalence of disability increases. You might also be wondering why some of the cells have the letter E next to their data...

Data quality indicators

The answer is: data quality indicators.

Statistics Canada uses several letters or symbols to indicate data quality or other important information about a data point or estimate in their data tables.

Some of the commonly used letters or symbols include:

"X": Indicates that the estimate has been suppressed to meet the requirements of the Statistics Act.

"E": indicates that the estimate has a high level of sampling variability and should be interpreted with caution.

"F": indicates that the estimate is too unreliable to be published.

These letters or symbols provide important information about the quality and reliability of the estimates in the data table, and help users to make informed decisions about how to interpret and use the data.

Recap of key points

In summary, in this video we went through three key components of understanding data tables, why a data table is important, how a data table is structured, and how to interpret data quality indicators.

(The Canada Wordmark appears.)