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Null Hypothesis / Alternate Hypothesis

I am still confused about these.

Our poll says that candidate A is ahead of candidate B 52/48. What is the Null, what is the Alternate?

- Robert



Edited 1 time(s). Last edit at Friday, October 15, 2010 at 02:19AM by Robert A.

Let me clarify my question.

ONE
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I'm a medical researcher. I want to prove that a new drug is effective for treating a certain disease.

In setting up an hypothesis, there are two possible outcomes: The drug is effective in treating the disease, or the drug is not effective in treating the disease.

Which outcome is my null and which outcome is my alternate?

TWO
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For years, it has been widely accepted that salt intake has no effect on weight. I believe this is incorrect and want to prove otherwise.

Which is the null hypothesis, that salt intake has no effect on weight, or that it does have an effect on weight?

Thank you,
Robert

- Robert

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So, it's the alternative that I hope to prove true?

That is, Ha is true if the drug is effective, or that salt intake is related to weight gain?

- Robert

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Another attempt to understand this....

You're prosecuting a case against a criminal defendant. You're trying to prove he's guilty of a crime. Are you trying to prove Ha (the alternate)?

- Robert

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Yes.

Let's say you want to prove the drug is effective. You would go:

H0=The drug isn't effective
H1=The drug is effective

So when you are able to reject H0 you can assure with a XX% confidence that the alternative (H1) is true, i.e. the drug is effective. If you are not able to reject H0 you just can't say anything about whether the drug it's effective or not.

The key is to know that you can prove H0 wrong, but never prove it true. Therefore, the statement you want to prove true must be H1.

In short:
-H1 is always the statement you hope to prove true.
-You can reject H0 => H1 is true // You can't reject H0 => you know nothing.

Just remember that and you'll be fine.

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Thanks. That clears a lot of confusion on the matter.

I'm a L2 candidate and I completely misunderstood this whole topic in L1. Ironically, I passed quant >70, probably by luck.

Now I have the time to learn it properly -- it comes up in L2.

- Robert

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Great stuff Fdez!

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"So when you are able to reject H0 you can assure with a XX% confidence that the alternative (H1) is true, i.e. the drug is effective"

Just to muck things up a bit - When you reject H0, you are really saying that if H0 is true then you have drawn a sample so contrary to H0 that it would only happen 100*alpha % of the time. If H1 is the "omnibus" alternative (i.e., the one that includes everything that's not in H0) then either a rare event has happened or H1 is true. At some point (usu alpha = 0.05) we conclude that H0 is false because events rarer than 5% just aren't morally likely or something (We use 0.05 because RA Fischer one time said that 0.05 is no less arbitrary than any other number so we might as well use it).

The reason you can't exactly say that there is some probability that H1 is true is that H1 isn't a random event so it doesn't have probabilities associated with it.

Unless you're a Bayesian. And then you can say that stuff.

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