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I have a set of data that looks like this:

Person 1 [48 total records] 2, 2, 2, 1, 2, 2, 1, 2, 1, 2, 1, 2, 2, 2, 1, 1, 1, 2, 1, 2, 2, 1, 2, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2, 1, 1, 2, 2, 2, 2, 1, 1, 2, 2, 1, 2, 1, 1, 1, -- Person 2 [56 total records] 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 1, 2, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 1, 2, 2, 2, 2, 2, 2, 2, 1, 2, 1, 1, 1, 1, 2, 1, -- Person 3 [18 total records] 1, 2, 1, 2, 1, 1, 1, 1, 2, 2, 1, 2, 2, 2, 1, 1, 1, 1, 

A '1' indicates a false answer, and a '2' indicates a correct one. I want to be able to compare records to see if any people in the data set are performing significantly above or below average. I've heard of using z-scores and standard deviation, but I'm not sure if that's the correct approach, or even how I would go about doing the calculation.

I also need to find out the minimum number of records I would need in order to have sufficient confidence in the results.

My math skills are pretty limited, so a simple explanation would be greatly appreciated.

  • 0
    I thought significance was a technical term that indicates whether the product indicates a pattern, rather than just chance. Or am I confusing it with confidence levels?2012-08-16

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How about a very simple solution that can give you kind of an overview?

  1. for each person, calculate the percentage of correct answers (= the number of 2's / total records).
  2. group these numbers into groups, e.g. 0-10%, 10-20%, .... Count the numbers in each group. This gives you an overview of how people perform, e.g. 6/10 people belongs to the 80-90% group and 4/10 in the 20-30%.
  • 0
    Is there a reason why the "significance" approach is a problem? I thought significance was a technical term that indicates whether the product indicates a pattern, rather than just chance.2012-08-16