Cherry-Picking
You can prove almost anything if you get to choose which evidence counts.
Cherry-picking means selecting the data points, studies, or examples that support your conclusion while quietly ignoring the ones that don't. It's not lying — everything you present might be accurate. The distortion comes from what you leave out. Show three studies that support a drug's effectiveness, don't mention the seven that found no effect, and you've built a technically honest but deeply misleading case.
This happens everywhere. A company cites favourable research while burying negative trials. A politician quotes the economic statistic that supports their argument while ignoring the one that contradicts it. A health influencer shares the one study that matches their recommendation and skips the systematic review that disagrees. In each case, the audience sees real evidence — just not the full picture.
The problem is that you often can't tell when it's happening. You'd need to know what evidence exists, not just what evidence you've been shown. That's why systematic reviews and meta-analyses matter: they attempt to include all available research, not just the convenient parts. And it's why anyone making a strong claim from a handful of selected sources deserves extra scrutiny. The strength of an argument isn't in the evidence presented. It's in the evidence that survives when you include everything.
References
- Ben Goldacre — Bad Science (2008)
- John Ioannidis — Why Most Published Research Findings Are False (2005)