Quantitative Usability, Statistics & Six Sigma by Jeff Sauro
Sample Size Calculator for Discovering Problems in a User Interface
by Jeff Sauro | October 1, 2006 ::
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Sample Size from an estimate of Problem Occurrence (p)
If the probability of detecting a UI problem is known in advance, use this portion of the calculator to estimate the total number of users needed to uncover on average the specified percentage of problems (e.g. 90%). The calculator is based on the binomial probability formula.
Estimate Problem Occurrence (p) then Sample
Size
This portion of the calculator first builds
an estimate of the probability of detecting a UI problem (from sample
data). It then produces an estimate of the number of users needed
to discover the specified percent of total problems. It uses the Good-Turing
and Normalization procedure as outlined by Lewis (2001)
and further discussed in (Turner, Lewis & Nielsen
2006).
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Lewis, James (2001) "Evaluation of Procedures for Adjusting Problm-Discovery Rates Estimated from Small Samples" in The International Journal of Human-Computer Interaction 13(4) p. 445-479
Turner, C. W., Lewis, J. R., and Nielsen, J. (2006). Determining usability test sample size. In W. Karwowski (Ed.), International Encyclopedia of Ergonomics and Human Factors (pp. 3084-3088). Boca Raton, FL: CRC Press.
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| June 17, 2009 | Davant G Bryant wrote: |
| 6. Why is population shape of concern when estimating a mean? What does sample size have to do with it? |
| April 30, 2008 | Raul R Wells wrote: |
| Very useful, I could not move the bar, so it reported 50% against a 100% I wished to mark |
| January 4, 2008 | John Romadka wrote: |
| It might help if you could give a real world example of how these calculators could be used. Because I think I get it, but an example would make it more concrete. |
| January 4, 2008 | John Romadka wrote: |
| Jeff, I wonder if you could add a little contextual help for the Problem Occurance field (".30"). Specifically, when would I use a number closer to 0 or a number closer to 1. |