RM>Inferences are sometimes correct, but often
RM>incorrect as well.  I don't think this is a good way to
RM>operate if you have an alternative process available.
DT>And what is the alternative process?
REAL research... Take what you're calling a "study", make
sure it limits variables as much as possible, repeat it to
verify results, then try modifying the variables (run an 
experiment) to determine the dependencies, etc...
DT>Do you mean that only Qualitative research is to be 
DT>considered reliable?
First of all, I think you mean quantitative, and, no, it
isn't essential to be numerical (though that often helps),
but it IS essential that it be RESEARCH and not unstructured
observation....
DT>I think others have argued that research in general can be slanted 
DT>to prove this or that theory.
Research can't be slanted if it is performed properly.. DATA 
can often be interpreted "creatively" if one wishes to do so,
however...  Usually, this creative interpretation applies to
"studies" more so than to research, simply because research
has very little "wiggle room".  Usually the worst that can
happen with research is to come up with no clear conclusion.
Studies often have MANY variables involved, some hidden, and
"conclusions" are often suspect, imo... The vagueness of what
is being tested allows one great latitude in inferring what
the results mean....
I guess I have to point out that for me, research involves 
scientific method, not simply thrashing about hoping to
stumble across something by collecting observations more or
less randomly...
DT>If I understand you correctly I am assuming that you refer to single, 
DT>unsupported research when you say that conclusions are inferential.
Yes, certainly that, but also studies that are not 
formulated in a scientific way...  Part of our problem
here is our different interpretations of "research" and
"studies"...
DT>We can confidently go beyond mere inferences when a large body of 
DT>research brings us to the same or similar conclusions.  
I think our confidence in the DATA improves, but the meaning
of the data is in question if the process of collecting it
is haphazard...  For example... 
Suppose an alien wished to draw conclusions about human 
behavior.  Each day "he" goes out and observes humans.  Does 
it in a few cities, towns, etc.  Someone else repeats the 
study.  End result is a list of activities of humans.  The 
list DOESN'T include sleeping (which occupies a large part 
of a human's day).... Why?  Observations were not conducted
scientifically, and no one thought to vary the time of the
observations to include night.  Are the conclusions valid?
Does it matter how many times "they" repeat the study?  A
flawed study is suspect (as is flawed research).  Now this
is an extreme illustration, admittedly, but the principle
applies to a lesser degree in almost any study, and to
some research as well (but at least with research, an effort
is made to catch all these little details)...
DT>... it can also be said that it is unnecessary to run an 
DT>experiment every time one conducts a study.
Absolutely, as long as one realizes that any conclusions
are questionable and unverified without running further
tests, and conducting experiments which modify variables.
DT>Not every study requires an experiment or control groups.
Then, frankly, any conclusions that one may be tempted to
draw as a result are meaningless....
DT>Qualitative research methods are employed not out of convenience or 
DT>expediency, but because that which is being studied can best be examined 
DT>using a qualitative research approach.
Now here I'm at a loss.... Qualitative is non-numerical..
Previously it appeared that you were confusing qualitative
with quantitative, but in this context I'm not so sure..
Some things do not easily lend themselves to quantification.
Emotions, for example...  Most research IS quantified simply
because quantification conveys additional information (A is
related to B is not as good as A = 2*B)... We always seek

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