Date: Wed, 9 Oct 2002 16:43:14 -0600
Reply-To: Geoff Matthews <geoff.matthews@waterford.org>
Sender: "SPSSX(r) Discussion" <SPSSX-L@LISTSERV.UGA.EDU>
From: Geoff Matthews <geoff.matthews@waterford.org>
Subject: Re: Sample vs Population
Content-Type: text/plain; charset="US-ASCII"
That's a great response rate, and high enough that inferences made from
it are very reliable.
At least according to Dillman and "The Total Design Method."
Geoff Matthews
-----Original Message-----
From: Alison Neustrom [mailto:alison@blueprintrd.com]
Sent: Wednesday, October 09, 2002 4:38 PM
To: SPSSX-L@LISTSERV.UGA.EDU
Subject: Re: Sample vs Population
What would you say if you had 80% of a non-random sample of a population
(I sent them to everyone but only got back 80%)? Would you consider that
a sample or a population?
-----Original Message-----
From: SPSSX(r) Discussion [mailto:SPSSX-L@LISTSERV.UGA.EDU]On Behalf Of
Jelani Mandara
Sent: Wednesday, October 09, 2002 11:50 AM
To: SPSSX-L@LISTSERV.UGA.EDU
Subject: Re: Sample vs Population
Fink, Steven wrote:
>Recently, I've been asked by several analysts about analyzing
>populations,
that is, data not from a sample.
>
>The purpose of a statistical test is to make estimates about the
population. If my data set IS the population, are significant tests
appropriate?
>
>
>
No. Descriptives and Effect Sizes are still relevant, but not
inferential stats.
>
>
>What about if my response rate (survey/unit) is low, say 20%. For
>example,
I sent surveys to everyone in the population, but only received 20% of
responses. Does this change your answer to the first question?
>
>
>
>
Then you only have a (probably nonrandom) sample of the population. The
logic of inferential stats applies.
>Thanks
>
>
>
>Steve
>
>
>
--
Jelani Mandara
Assistant Professor
Human Development and Social Policy
Northwestern University
2120 Campus Drive
Evanston, Il 60208
Office Phone: (847)491-3122
Web Page: http://www.sesp.northwestern.edu/people/sp/j_mandara.html
