Fighting Misinformation
Catalogue number: 892000062025001
Release date: December 15, 2025
In today's information environment, numbers can spread quickly, but not all data is collected or analyzed the same way. By thinking critically about data, you can avoid being misled to make smarter and more informed decisions.
- Data journey step
- Foundation
- Data competency
-
- Data ethics
- Evaluating decisions based on data
- Evidence based decision-making
- Audience
- Beginner
- Suggested prerequisites
- N/A
- Length
- 7:54
- Cost
- Free
Watch the video
Fighting Misinformation - Transcript
Meet Robert.
He's a project manager, which means his job is to keep projects on track, creating reports, managing tasks, and leading his team. Sometimes he also needs to analyze data to make informed decisions.
Recently, Robert was asked to brief his director on food insecurity in Canada. His team brought him a report they found online. It claimed that 38% of Canadians faced food insecurity in 2024.
In today's information environment, numbers can spread quickly, but not all data is collected or analyzed the same way.
So before using the 38% figure, Robert wonders:
- Could sharing it without checking risk spreading misinformation?
- Who came up with this number?
- How is it calculated?
- Can we trust it?
Before presenting this information to senior management, Robert knows he needs to dig deeper.
Step one: Check the data source and survey design.
Robert starts by looking at where the data came from. The 38% statistic was based on an online survey which sampled 5,000 people. Right away, Robert notices some red flags.
- The report doesn't say how many people were chosen. Were they selected randomly or did they volunteer? Random selection is important for unbiased results.
- Also, there's no breakdown of who responded. No details on their age, location, or background. This makes it unclear if they represent all Canadians.
- The report doesn't mention the response rate either. Out of the 5,000 people contacted, how many actually filled out the survey? A low response rate can make results less reliable.
- And finally, the definition of food insecurity isn't explained. What exactly does this online survey consider as food insecurity?
To compare, Robert looks at data from Statistics Canada's Canadian Income Survey. This annual survey collects information on various topics including food insecurity in 2022. This survey used a much larger sample, 60,000 households and had a 70% response rate.
It found that 23% of Canadians experienced food insecurity. This number is much lower than the online survey, at 38%. Robert realizes he needs to find out why.
Step two: Compare how food insecurity was measured.
To understand the difference, Robert looks at how each survey define food insecurity.
Statistics Canada defines food insecurity as the ability to acquire or consume an adequate diet quality or sufficient quantity of food in socially acceptable ways, or the uncertainty that one will be able to do so.
The Canadian Income Survey asks 18 questions to measure food insecurity, such as worrying about running out of food before getting money to buy more, skipping meals due to financial constraints, and going an entire day without eating.
The online survey, on the other hand, did not provide the definition of food insecurity and used only one question to measure it in the past year.
Have you ever worried about running out of food?
So what's wrong with this one question approach?
Well, first, it only measures worry, not actual experience. So someone might fear running out of food but never actually run out.
And second, it lacks detail. It doesn't ask how often this happened or whether the person actually struggled with food insecurity.
Because of these weaknesses, Robert doesn't trust the 30% statistic. However, he still wants to make sure the 23% figure from Statistics Canada is accurate.
Step three: Check if the data is up to date.
Robert considers when the data was collected. Statistics Canada survey is from 2022, but it's now 2025. The online survey data was collected in 2024, which is more recent. That's why Robert's team wanted to use it.
But even though the StatCan data is older, Robert decides to stick with it because it's based on better data. Still, he notes in his report that newer numbers will come out soon, since the Canadian Income Survey is conducted annually and those numbers should be checked once available.
Step four: Look at trends over time to get a better picture.
Robert looks at food insecurity data from past years.
- In 2020, which was a pandemic year, 16% of Canadians experienced food insecurity.
- In 2021, there was a slight uptick to 18% after financial aid programs ended.
- Then in 2022, 23%, a further increase as economic challenges continued.
Since the 23% in 2022 continues a short term trend that aligns with the economic conditions Canadians have faced since the onset of the pandemic, Robert believes this estimate is reasonable.
Meanwhile, the online survey doesn't provide past estimates, so there's no way to check if their 38% is part of a trend or just an outlier.
This reinforces Robert's decision to trust Statistics Canada's numbers over the online survey. Robert doesn't analyze data every day, but when it matters, he takes the time to make sure it's sensible. His critical thinking prevents misleading numbers from influencing important policy decisions.
After all, good decisions depend on good data, and good data comes from proper methods and careful analysis.
So even if you're not a project manager, you're still exposed to statistics all the time on social media, in news reports, and in school.
Not all numbers are reliable, so it's important to question where they come from and how they were obtained. Next time you see a surprising statistic, ask yourself:
- Who conducted this survey? (Is it from a trustworthy source?)
- How many people participated? (Was the sample large enough and what was the response rate?)
- How were participants chosen? (Was the selection process unbiased?)
- How were questions asked? (Did they capture the concept properly?)
- And finally, how recent is the data? (Is it still relevant?)
By asking these questions, you can help avoid the spread of misinformation.
And remember by thinking critically about data,you can avoid being misled and make smarter, more informed decisions.
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