Parametric and non-parametric tests?!

 Parametric and non-parametric tests?!
Posted: Wednesday, October 11, 2017 @ 04:40 PM
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Joined: 10 September 2012
Posts: 25

Can someone tell me the difference between the two? The textbook isn't very clear on this so far! Thanks!

Posted: Wednesday, October 11, 2017 @ 06:19 PM
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Joined: 8 December 2008
Posts: 723

Parametric tests are more robust than non-parametric tests.  This means that they are more powerful - they are more likely to correctly identify a significant difference when there is one, and therefore the greater power they have in correctly rejecting the null hypothesis  This means there is less likelihood of a type one or type two error.

Parametric tests have more power than non-parametric tests because they have more information about the data and populations from which the sample is drawn (normally distributed sample and an interval (at least) level of measurement for the data).  Also more sophisticated mathematical calculations can be done with interval level data.  I hope this makes sense.

Another criteria is homogeneity of variance, but I have never really bothered explaining this to students in any detail unless they ask - it just means the standard deviations of the 2 sets of data are similar. 

Posted: Wednesday, October 11, 2017 @ 06:55 PM
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Joined: 19 October 2007
Posts: 82

Do they need to know the difference? The terms parametric and non parametric are not on the spec, although I appreciate the different stats tests can be called parametric and non parametric. 

Posted: Thursday, October 12, 2017 @ 09:38 AM
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I have taken the view as the terms are not on the AQA spec they cannot be questioned directly about para/ nonpara. Therefore to keep things as simple as possible I have avoided all mention of the distinction. Looking at this year's papers and mark schemes I was happy with that decision and will do the same this year.

Posted: Sunday, October 15, 2017 @ 01:49 PM
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Joined: 10 September 2012
Posts: 25

Thank you! I have always wondered what H.O.V means! Now I know . . .!