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Reply #50: a brief glossary [View All]

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foo_bar Donating Member (1000+ posts) Send PM | Profile | Ignore Wed Jun-15-05 03:43 PM
Response to Reply #46
50. a brief glossary
binomial variable:

Example 1
If 6 patients are treated with a newcream, interest may be in the number cured rather than the order in which they were cured. We use a variable X to represent the count. X can take the values 0,1,2,3,4,5,6, and we represent the probability of 2 cures by P(X = 2) or p2.

Example 2
If items on the shelf are inspected until a defective item is discovered, we might use a variable X to represent the number of good items we had to inspect. X can take the values 0,1,2,3,, with different probabilities.

Example 3
If X counts the number of prescriptions for a rarely prescribed drug over a week, X can take the values 0,1,2,3,, with different probabilities.

Example 1 is a particular case of the Binomial variable (under certain conditions) . . . . Examples 2 and 3 are not binomial.
an elementary stats course

anecdotes:

As the name suggests, anecdotal evidence is evidence for a claim which is based on remembered anecdotes either first hand from the speaker or second hand from others. Such evidence is often used to justify empirically verifiable claims. This is fine and even appropriate in the case that the claim is of little importance or in the case that it is reasonable to believe that few observations with little precision are needed as basis for a claim. Often, however, anecdotal evidence is used as backing for sweeping claims about a wide class of things, like natural phenomena or the behavior of people, which are the sort of claims usually examined by science (natural science, life science, or social science).
some guy (anecdotal)

sample fixed in advance

should read: sample size fixed in advance. My bad.

If the box contains tickets labeled with numbers other than 0 and 1, the sample sum does not have a binomial distribution. If the number n of draws is not fixed in advance, the sample sum does not have a binomial distribution. If the draws are not independent, the sample sum does not have a binomial distribution. If the chance of drawing a ticket labeled "1" is not the same value p in each draw, the sample sum does not have a binomial distribution.
berkeley

This time the number of trials is not fixed in advance so X is not Binomial.
Stat 201 exam


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