I rather think the problem is not adequately defined; but that may
merely reflect the fact that it's a homework problem, and homework
problems often require highly simplifying assumptions in order to be
addressed at all. See comments below.
On Fri, 4 May 2001, Adil Abubakar wrote:
> My name is Adil Abubakar and i am a student and seek help. <snip>
> if anyone can help, please respond to [EMAIL PROTECTED]
>
> Person A did research on a total of 4500 people and got the following
> results:
>
> Q. 1. How many hours do you spend on the web?
> 0-7 8-15 15+
> 18% 48% 34%
>
> Q. 2. Do you read a privacy policy before signing on to a web site?
>
> 1=Strongly Agree 2=Agree 3=Neutral 4=disagree 5=strongly disagree
> 9% 17% 20% 32% 22%
If this were a research situation, or intended to reflect practical
realities, there would also be information about the relationship between
the answers to Q. 1 and the answers to Q. 2. This information might be
in the form of a two-way table of relative frequencies, or (with suitable
simplifying assumptions on the variables represented by Q.1 and Q.2) as a
ccorrelation coefficient. Without _some_ information about the joint
distribution, I do not see how one can hope to address the questions
posed below.
> Another person asked the same questions of 100 people and got the same
> results in % terms. Can it be shown via CI that the result is
> consistent with the expectations created by the previous survey?
If the % results were indeed the same (so that all differences in
corresponding %s were zero), it would not be necessary to use a CI (by
which I presume you mean "confidence interval") to show consistency.
(HOWEVER, even identical % results do not imply consistency, unless at
the same time the joint distribution were ALSO identical; and you do
not report information on this point.)
OTOH, if the results were merely similar but not identical, you would
want some means of assessing the strength of evidence that resides in the
empirical differences. That in turn depends on the assumptions you're
willing to make about the two variables: do you insist on treating the
responses as (ordered) categories, or would you be willing, at least pro
tempore, to assign (e.g.) codes 1, 2, 3 to the responses to Q. 1, use the
codes 1, 2, 3, 4, 5 supplied for Q. 2, and treat those values as though
they represented approximately equal intervals?
> Also can it be argued that the subjects have been subjected to the
> questions before?
Not sure what you mean by this question. If you know that the Ss have
indeed been asked these questions previously (are they perhaps a subset
of the original 4500?), no arguing is needed; although what this would
imply about the results is unclear. If you mean, do the identical (or at
least "consistent") results imply that the Ss must have encountered these
same questions previously, I do not see how that can be argued, at least
not without more information than you've so far provided. Perhaps more
to the point, why would such an argument be of interest?
> Can it be asserted with statistical significance, that if the survey
> is repeated on at least 100 people the result will [be] in the same
> proximity of the above survey??
No. I suggest you look closely at the definition of "statistical
significance": the term is quite incompatible with the assertion you
propose. (If you don't see that, you might bring a focussed version of
the question back to the list. If you do see that, you may still have
some question that is more or less in the same ball-park as the question
you've asked here, and you may wish to bring the revised question to our
attention.)
> any help ... will be appreciated. Just need the different
> methodologies.
Yes; but for which questions, exactly?
-- DFB.
------------------------------------------------------------------------
Donald F. Burrill [EMAIL PROTECTED]
348 Hyde Hall, Plymouth State College, [EMAIL PROTECTED]
MSC #29, Plymouth, NH 03264 603-535-2597
184 Nashua Road, Bedford, NH 03110 603-472-3742
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