A type of statistical test used with data that conform to parametric criteria. Parametric tests are calculated on actual scores anare therefore more sensitive than non-parametric tests.
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Powerful
They are sensitive to the features of the data collected, so more likely to detect statistically significant effects
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Comprehensive
They use all the information available (look at the size of differences and the values involved, not just the order of sizes)
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Robust
There are certain assumptions underlying their use, but it is possible to do a parametric test on data which do not fit the assumptions precisely
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Nominal level
(categorical data) where the unit of measurement refers to people or events in categories
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Ordinal level
Where the units of measurement can be ordered from lowest to highest, but the units are not of equal or defined size
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Interval level
Where the units of measurement are of equal or defined size
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Nominal distribution
Where most scores in a set cluster around the mean, with just a few at each extreme. A typical bell-shaped distribution
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Homogenous Variances
Where two setsof scores show a similar level of variability
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Other cards in this set
Card 2
Front
They are sensitive to the features of the data collected, so more likely to detect statistically significant effects
Back
Powerful
Card 3
Front
They use all the information available (look at the size of differences and the values involved, not just the order of sizes)
Back
Card 4
Front
There are certain assumptions underlying their use, but it is possible to do a parametric test on data which do not fit the assumptions precisely
Back
Card 5
Front
(categorical data) where the unit of measurement refers to people or events in categories
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