Re: New here questions on lyme and other
- From: Needsomeinput <needrealhelp61@xxxxxxxxx>
- Date: Wed, 20 Feb 2008 20:24:01 -0800 (PST)
On Feb 20, 7:28 pm, the 3rd Man <sir_de...@xxxxxxxxx> wrote:
On Feb 20, 5:20 pm, cowabungab...@xxxxxxxxx wrote:
Still think I'm right about the binomial
Ok, I didn't want to go further with this but the binomial theorem has
nothing to do in this situation.
Allright...try it this way, then, no math...logic. (Not wanting to
beat this to death, but...)...
And you are, for the sake of argument, saying that the existing tests
are no better than a 50-50 coin flip in detecting Lyme infection in
any given sample...ONE sample only, right? One given sample among a
population, right?
But, see...that is NOT what we are talking about here. Here we were
discussing the odds of getting the same result in the same individual
over repeated trials. NOT across an entire population.
as yet another example the probability of throwing one coin twice and
getting consecutive equal results is exactly the same as throwing 2
coins at the same time and both landing on the same side. You can do
the same with 3,4, 5 etc you get the point and how the probability for
that happening decreases.
For your binomial coin-flip thing to work...you need independent and
random events. While the odds of detecting Lyme in any given person
may be 50-50 (not at all sure that I accept this)...those are NOT the
odds for getting similar results in one person.
In reality the events have to be independent of each order for this
rule (multiplicity of probabilities) to apply, check:
http://library.thinkquest.org/11506/prules.html on the left side third
from the top. But in general just google the rule of independent
events and probability.
3rd I like your analysis but I think your perception of random and
inherent error (i.e. of a test) is not quite correct. I don't know
exactly how to explain this, I have to admit I'm not as eloquent as
you guys, but maybe an example can help: the p value that you see in
scientific abstracts to accept a difference between 2 groups (or
similarly but not exactly an ANOVA for several groups) is usually set
to <0.05 why? is subjective it means that the probability of the
difference between groups observed is due to "randomness" is 5% which
means that the probability of this being a "real" difference is 95%,
but some researchers can (and some do) set the cut-off at 0.1 (or
whatever but usually is not more than that) but 0.05 is just the
standard right now (and it would be up to the reader to accept that
degree of probability, assuming the author is using a different p
value cut-off). The p value depends on several things, number of
specimens per group, statistical distribution assumed (usually
Gaussian, two tailed in other words "bell shaped"), difference between
averages and standard deviation for each group.
.
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