This blog post is part of a series focusing on media literacy.
We love statistics. Specifically, we love raw number statistics: number of students proficient or advanced, number of babies named Emma, number of hot dogs eaten in 10 minutes, and more. We also love percentage statistics: grades; batting averages in baseball, women’s pay as a percentage of men’s pay, and so on. There is a certainty to these. Statistics are made of numbers, and numbers don’t lie.
But while numbers don’t lie, it is easy to use the statistics compiled from them in a biased way. The media literate person needs to understand how statistics can be manipulated—and that's where statistics literacy comes in. Let me offer a hypothetical example—followed by tips for educators and parents to teach students about statistics literacy in either the classroom or at home.
Hypothetical Example: I want my students to turn off all devices for one day—24 hours with no cellphone, no computer, no e-reader, no Xbox, no anything. I want them to see how addicted they are and how life can still continue without screen time. Let’s say I try this experiment with 100 students in three of my middle school classes. I toss out the idea on Monday and ask students on Tuesday how many succeeded. The answer? Only one. I spend some time Tuesday sharing some numbers with students about the average amount of screen time spent daily and the possible negative effects that may have. I repeat the challenge. On Wednesday, five students report that they turned off all devices for a day.
Bias in Selection
Let’s look at two reports using statistics from Tuesday and Wednesday:
The No Device Challenge is gaining traction. In only one day, five times as many students as the day before accepted the challenge. At this rate, in just two more days no students will have devices on.
The No Device Challenge is not gaining traction. After two days, 95% of students have failed to change their behavior.
Both reports are true. Both accurately report the numbers, and the statistics are correct. Yet they lead to opposite conclusions about how the project is going. The reporters selected different numbers to analyze. If you are biased in favor of this project, you will likely use the first report. If you are biased against this project, you will likely use the second.
Sneaking in Biased Words
Beware of descriptive adjectives added to statistical reports. Numbers are embedded in sentences and paragraphs, and the words used to introduce the numbers suggest bias:
The No Device Challenge is gaining traction. In only one day, an impressive five times as many students as the day before accepted the challenge.
The No Device Challenge is not gaining traction. After two days, a disappointing 95% of students have failed to change their behavior.
It is extremely common to see opinions such as these slipped into statistical reporting. Just one or two words can totally influence the way you read the numbers. Did the number of students surge up to five, or did the number of students barely budge from Day 1?
Bias in Graphs
Graphs are used in biased ways, too. Here’s a graph that makes the No Device project look great:
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