This is a remix of a bunch of posts. I brought them together because they fit a common theme: Examples that use actual data that researchers collected but still manage to lie or mislead with real data. So, lying with facts.
These examples hit upon a number of themes in my stats classes:
1) Statistics in the wild
2) Teaching our students to sniff out bad statistics
3) Vivid examples are easier to remember than boring examples.
Here we go:
Making Graphs
Fox News using accurate data and inaccurate charts to make unemployment look worse than it is.
Misleading with Central Tendency
The mean cost of a wedding in 2004 might have been $28K...if you assume that all couples used all possible services, and paid for all of the services. Also, maybe the median would have been the more appropriate measure to report.
Don't like the MPG for the vehicles you are manufacturing? Try testing your cars under ideal, non-real world conditions to fix that. Then get fined by the EPA.
Misleading with Sampling
78% of young women approve of a no-good man sexting women who aren't his wife? Well, that number is correct...if you sample sugar babies.
Autism is linked to vaccination. If you are a research with a conflict of interest who uses a small sample of people who are typically biased against vaccination AND don't demand any actual medical evidence of anything you are measuring.
Misleading with Probability
Absolute versus relative risk. Here, the way that perfectly accurate birth control safety data is presented affects birth control use, per Gerd Gigerenzer.
These examples hit upon a number of themes in my stats classes:
1) Statistics in the wild
2) Teaching our students to sniff out bad statistics
3) Vivid examples are easier to remember than boring examples.
Here we go:
Making Graphs
Fox News using accurate data and inaccurate charts to make unemployment look worse than it is.
Misleading with Central Tendency
The mean cost of a wedding in 2004 might have been $28K...if you assume that all couples used all possible services, and paid for all of the services. Also, maybe the median would have been the more appropriate measure to report.
Don't like the MPG for the vehicles you are manufacturing? Try testing your cars under ideal, non-real world conditions to fix that. Then get fined by the EPA.
Misleading with Sampling
78% of young women approve of a no-good man sexting women who aren't his wife? Well, that number is correct...if you sample sugar babies.
Autism is linked to vaccination. If you are a research with a conflict of interest who uses a small sample of people who are typically biased against vaccination AND don't demand any actual medical evidence of anything you are measuring.
Misleading with Probability
Absolute versus relative risk. Here, the way that perfectly accurate birth control safety data is presented affects birth control use, per Gerd Gigerenzer.
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