W4 Guidance on Parametric and Nonparametric Data

# W4 Guidance on Parametric and Nonparametric Data -...

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Guidance on Parametric and Nonparametric Data In RES/341 we learned about the four levels of measurement: nominal, ordinal, interval, and ratio. We know that as we go from nominal data to higher orders, we have increasing additional information about the data. For example, nominal is data that has classification but no order, distance, or origin. Ordinal data has classification and order, but no distance or unique origin. Interval data has classification, order, and distance, but no unique origin, Finally, ratio data has all four: classification, order, distance, and unique origin. Nonparametric data is essentially nominal and ordinal data. These are forms of data that have no shape of a population or classification. This data can not be measured in what is referred to as central tendency, that is determining the mean, mode and
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Unformatted text preview: median. ..terms that are coming soon. These data are at times referred to as "free of assumptions" regarding their distribution. Parametric data on the other hand, interval and ratio, are measurement levels in which the data can measure mean, median, and mode and other tests about the population they came from. ....and this last point is important. ...they (interval and ratio) have a population upon which they came from. Take another look at the four levels of measurement and their examples and try to answer the question, could I get an average from this data? Is this data from a population I can measure and compare? Please see the post “Levels of Measurement Summarized” in <Course Materials> that provide more descriptions of the levels of measurement....
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