Mark Kupferman's Blog » sample-size http://www.kupferman.com Kupferman.com is Mark Kupferman's home on the Internet featuring articles, reviews and comments on a variety of subjects. Sun, 19 Jun 2011 05:42:54 +0000 en hourly 1 http://wordpress.org/?v=3.2.1 Great Statistical Resource: The Analysis Factor StatChat http://www.kupferman.com/statchat-statistics-resources-blog.htm http://www.kupferman.com/statchat-statistics-resources-blog.htm#comments Fri, 10 Oct 2008 16:29:33 +0000 Mark Kupferman http://www.marketresearchtech.com/?p=179 Continue reading →]]> Statistical consultant Karen Grace-Martin launched a new blog in July, 2008 called “StatChat” which makes a lot of relevant, important, but sometimes hard to grasp statistical concepts easy to understand. Categories of postings include linear regression, missing data, spss, sas, anova, factor analysis, and sample size — things that all market research deal with on a regular basis (whether they like it or not!).

Karen is the founder and president of The Analysis Factor, a professional statistical consulting firm. Karen holds advanced degrees in both applied statistics and social psychology. She was a professional statistical consultant at Cornell University for seven years before founding her own company, and has taught statistics at the University of California Santa Barbara and Santa Barbara City College. She has also co-written an introductory statistics textbook called Data Analysis with SPSS.

http://www.analysisfactor.com/statchat/

]]> http://www.kupferman.com/statchat-statistics-resources-blog.htm/feed 0 How big should your sample be? http://www.kupferman.com/sample-size-overview.htm http://www.kupferman.com/sample-size-overview.htm#comments Sat, 09 Dec 2006 05:58:00 +0000 Mark Kupferman http://www.kupferman.com/blog/?p=82 Continue reading →]]> Is it enough to survey 100 people or are you only going to get useful results if you survey 1,000 people? The answer, unfortunately, really depends on the questions you are asking, the likely results, and your preferred "margin of error" (the +/- 3% or +/- 4% you see posted with most survey results). You basically need this information so you can reliably know whether that 4% difference between the two bars on your graph mean anything or not.

Personally, when I’m conducting an online survey I tend to prefer a sample of 1,000. In an overall sense it is usually overkill, but it usually allows me to segment the results in a number of different ways — I can break the results down by age group, gender, income, etc — something I couldn’t necessarily do if I started from a much smaller sample. I suppose it is the luxury of having access to a large respondent base — I can afford to oversample. Believe me, if I were paying $10 a response (like what I sometimes have to do when I rent a panel of people in another country) I am much more conservative in my sample sizes and pay really close attention to my margin of error and the needs of the study.

There are some web sites out there that make margin of error more understandable. The Red River College Marketing Research blog recently pointed to an article at www.isixsigma.com entitled "Margins of Error Made Easy!" which I found to be worth reading.

There are also several sample size calculators out there (you can find them by typing "sample size calculator" into Google). One that appears especially handy is at dssResearch.com. Grapentime.com offers not just a sample size calculator, but also a sample size calculator for attribute ratings (in other words, it tells you the minimum sample sizes you need for different type of metric mesasurement scales).

Margins of Error Made Easy at Isixsigma.com
Sample size calculator at dssResearch.com
Sample Size Calculator for Attribute Ratings at Grapentine.com

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