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Linebach, Jared A., Kovacsiss, Lea M., Tesch, Brian P. - Nonparametric Statistics for Applied Research
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Schrijver: | Linebach, Jared A., Kovacsiss, Lea M., Tesch, Brian P. |
Titel: | Nonparametric Statistics for Applied Research |
ISBN: | 9781461490401 |
Uitgever: | Springer US |
Bijzonderheid: | 2013 420pp Gebonden |
Prijs: |
€ 58,20
Gratis
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Meer info | Annotatie p Non-parametric methods are widely used for studying populations that take on a ranked order (such as movie reviews receiving one to four stars). The use of non-parametric methods may be necessary when data have a ranking but no clear numerical interpretation, such as when assessing preferences. I Flaptekst ¿¿Non-parametric methods are widely used for studying populations that take on a ranked order (such as movie reviews receiving one to four stars). The use of non-parametric methods may be necessary when data have a ranking but no clear numerical interpretation, such as when assessing preferences. In terms of levels of measurement, non-parametric methods result in ordinal data. As non-parametric methods make fewer assumptions, their applicability is much wider than the corresponding parametric methods. In particular, they may be applied in situations where less is known about the application in question. Also, due to the reliance on fewer assumptions, non-parametric methods are more robust. Non-parametric methods have many popular applications, and are widely used in research in the fields of the behavioral sciences and biomedicine. |
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