what is a "null hypothesis"?
The null hypothesis is a hypothesis which the researcher tries to disprove, reject or nullify.
very good; is it: 1. the same as the original claim? 2. different from the original claim? 3. depends on how it is stated :)
different
ideally that would be a nice condition. But if the original claim contains an equality, the the null hypothesis is the original claim. If the original claim is an inequality, the null becomes the opposite.
agreed.....can you help me with something?
i can try
A large pond is stocked with fish. The fish population P is modeled by the formula P = 2t + 8(sqrt of t)+ 140, where t is the number of days since the fish were first introduced into the pond. How many days will it take for the fish population to reach 500? (Round your answer to the nearest whole number.)
500 = 2t +8sqrt(t) +140 0 = 2t +8sqrt(t) +140-500 0 = 2t +8sqrt(t) -360 360 -2t ------- = sqrt(t) ; ^2 both sides 8 (45 - t/4)^2 = t 2025 + t^2/16 -90/4t = t 2025 + t^2/16 -86/4t = 0 ... this might go quicker with a wolframalpha :)
abt 133.741
134 perhaps; but lets dbl chk
134 is pretty good
I think a better way of putting it is, the null hypothesis holds when the data is not statistically significant.
It is the condition where the data doesn't show any scientifically interesting results.
right, the null can happen by chance then right?
Suppose you have a sample of smokers and a scientist wants to show that smoking is correlated to a rise in cancer rates. They need to show that there are more cases of cancer than can be explained by what would normally be expected in a randomly selected group of people.
They are disproving the null hypothesis, where the null hypothesis would be that there is no correlation and the rates are what would be expected from a randomly sampled group of people.
That makes sense if you are trying to support a claim that contains an inequality such as more than, greater than, less than .... but what about a claim of equality?
Can you give me an example of what you mean?
hmm .... the mean body temperature of healthy adults is equal to 98.6.
Statistical significance comes from looking for meaningful deviations from the mean. That means greater or less than. Its silly to say that something is statistically significant if it is equal to or close to the mean.
ok ... which is prolly why you dont find alot of nulls that are equal to the claim.
we were going over the hypthesis testing stuff in stats and the null/alternative section seemed backwards to me :) its making better sense now tho
Its just the "fallback" so to speak if you can't prove anything interesting is happening in the data.
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