Statistics can be unintuitive. What’s a large difference? What’s a large sample size? When is something statistically significant? You might think you know, based on experience and intuition, but you really don’t know until you actually run the analysis. You must run the proper statistical tests to know what the data are telling you.
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Even experts can get tripped up by their hunches, as we’ll see.
In my family, we’re huge fans of Discovery’s MythBusters. This fun show mixes science and experiments to prove or disprove various myths, urban legends, and popular beliefs. Are Daddy Longleg spiders really super-poisonous? Can diving underwater protect you from an explosion, or being shot? Are toilets really the cleanest place in the house? What is the fastest way to cool a beer? They often find a way to work in impressive explosions, one of their hallmarks. Thanks to MythBusters, my 7-year-old daughter was able to explain to me that you can identify the explosive ANFO because it’s made out of pellets!
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Comments
What is the point
I am failing to see the point of this article, other then stating the program "myhtbusters" is not factual/accurate enough and to promote your software? or was this the actual point?
Your analyses has a flawed assumption => The goal of the show is not to provide sientific data. It's goal is to make interesting viewing material for people, to ensure more people watch it, with the aim of making more money. For that goal, their selected sample size is big enough :-)
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