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This is way too much for the layman and full of mathematical language. What is null hypothesis? What is "at least as extreme as"? What is probability? Never

by sbov 11y ago

This is way too much for the layman and full of mathematical language. What is null hypothesis? What is "at least as extreme as"? What is probability? Nevermind that the null hypothesis forces us to think in double negatives, which isn't the most intuitive. It also isn't clear to me how you would apply your example given how most p-values are used. I read an article that says exercising makes you richer with a 95% confidence. So, as a layman, if I attempt to apply your example, it leads me directly into a common p-value mistake: the probability of me becoming richer if I exercise. 95%, right? Wrong!

elbigbad 11y ago
To be fair, this isn't "my" example. I selected it from the book above as a pretty good example from the book targeting p-value, the subject of this thread. It is part of a larger scheme of examples and explanations in the book. The book itself goes through and clears up things like "null hypothesis" and "at least as extreme as" using other examples. That one quote wasn't really meant to take the layman from zero to "p-value master" in a handful of sentences.
ewzimm 11y ago
I'm having a hard time understanding why p-values are so hard to explain without resorting to jargon... it seems very intuitive to me, and none of these examples really put it in context. I'd explain it like this: It's easy to lie with statistics if you take them out of context. Maybe I have an idea that drinking flouridated water causes cancer, so I take a survey and find that 40% of people who drink flouridated water develop cancer. That number is meaningless without knowing how likely it is for people who don't drink it to develop cancer, which is about 40%, so the numbers match up 1:1, completely normal. In this case, 1 is the p-value, and it gives you a starting point for developing an experiment.
- nonbel 11y ago
  >"That number is meaningless without knowing how likely it is for people who don't drink it to develop cancer, which is about 40%. That's the p-value, and it gives you a starting point for developing an experiment." That is the frequency of cancer given not drinking fluoridated water. That is not a p-value.
  - ewzimm 11y ago
    Sorry, I saw how that could be misleading by saying that's so I clarified right away... not fast enough I see. I mean that comparing the observed data to a baseline gives you a p-value.
    - nonbel 11y ago
      This example is still misleading because you have selected a special case where the frequencies are exactly equal. In any other case the p value will depend on the sample size.
      - ewzimm 11y ago
        True, but what I'm trying to convey is that if someone just wants to generally understand what a p-value is from no knowledge, understanding how to read a specific number isn't important. At first, I wasn't even going to include a specific number, but I realized not having one would be confusing in its own way. Looking at a specific p-value and understanding its significance is only useful once they're actually looking at a study. But first they just want to know how it's derived and what it's good for.

by sbov 11y ago

elbigbad 11y ago

To be fair, this isn't "my" example. I selected it from the book above as a pretty good example from the book targeting p-value, the subject of this thread. It is part of a larger scheme of examples and explanations in the book. The book itself goes through and clears up things like "null hypothesis" and "at least as extreme as" using other examples. That one quote wasn't really meant to take the layman from zero to "p-value master" in a handful of sentences.

ewzimm 11y ago

I'm having a hard time understanding why p-values are so hard to explain without resorting to jargon... it seems very intuitive to me, and none of these examples really put it in context. I'd explain it like this: It's easy to lie with statistics if you take them out of context. Maybe I have an idea that drinking flouridated water causes cancer, so I take a survey and find that 40% of people who drink flouridated water develop cancer. That number is meaningless without knowing how likely it is for people who don't drink it to develop cancer, which is about 40%, so the numbers match up 1:1, completely normal. In this case, 1 is the p-value, and it gives you a starting point for developing an experiment.

nonbel 11y ago
>"That number is meaningless without knowing how likely it is for people who don't drink it to develop cancer, which is about 40%. That's the p-value, and it gives you a starting point for developing an experiment." That is the frequency of cancer given not drinking fluoridated water. That is not a p-value.
- ewzimm 11y ago
  Sorry, I saw how that could be misleading by saying that's so I clarified right away... not fast enough I see. I mean that comparing the observed data to a baseline gives you a p-value.
  - nonbel 11y ago
    This example is still misleading because you have selected a special case where the frequencies are exactly equal. In any other case the p value will depend on the sample size.
    - ewzimm 11y ago
      True, but what I'm trying to convey is that if someone just wants to generally understand what a p-value is from no knowledge, understanding how to read a specific number isn't important. At first, I wasn't even going to include a specific number, but I realized not having one would be confusing in its own way. Looking at a specific p-value and understanding its significance is only useful once they're actually looking at a study. But first they just want to know how it's derived and what it's good for.