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Graphic presentation of data & understanding of stats can be a matter of life & death. Just learned something: Those Hurricane Maps Don’t Mean What You Think They Mean - The New York Times https://www.nytimes.com/interactive/2019/08/29/opinion/hurricane-dorian-forecast-map.html
According to the Times description, those maps are basically confidence intervals -- which almost everyone, including social scientists, misunderstand (just like they misunderstand statistical significance).
"Significance" in a null hypothesis test, e.g., .05, isn't the probability there's an effect given the data (a Bayesian posterior). It's the prob of getting the data given there's no effect (a likelihood). Study: 80% of profs teaching stats get this wrong. http://www.onemol.org.uk/Gigerenzer-2004.pdf
Similarly, a 95% confidence interval doesn't mean there's a .95 prob the true value is somewhere inside it (a Bayesian concept). It means 95% of the time you've placed the interval over the true value (given several assumptions). Not the same thing.
Hurricane maps don't show the probable path of the eye + size of the storm. They are regions that are likely to include the storm, & fatten over time because our uncertainty, not the storm, grows. An important distinction. Excellent illustrations in the NYT article.
