Null means null. A terifying habit is to state in error that the primary hypothesis is null when it is not. For example:
Dennis Roberts <[EMAIL PROTECTED]> wrote:
"I would say the null is .75 ..."
Geez Phillip ... so sorry if I terrified you or anyone else.
And I am willing to admit I was in error and that we should say that H(1) is .75 in this case. However, as you say below ... one has to convert the hypothesis to a null form ... pray tell what will that null be in this case? Will we just toss out 50/50 ... ??? Where's the logic in that? This is precisely why ... formulated nulls in most cases are meaningless.
One "could" argue that the null is that there is no difference between drive thru and inside sales ... ie, p and q are .5 ... if that is the case, then the alternative is that it is not 50/50 ... it's not that it is .75. Thus, when it is stated as .75 ... I don't really see a null that goes along with that.
What I would do in this case is to build a 95% CI based on the given data over the 50 days ... and see if .75 is inside or outside of that CI.
Thus, I will test the .75 against the CI ... but I don't (now that you have corrected me) have a clue as to what the null would be. So, what I am asking you is ... what IS the null in this case? What hypothesis (just one) are we trying to nullify?
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Dennis Roberts
[EMAIL PROTECTED]
http://www.personal.psu.edu/users/d/m/dmr/droberts.htm
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