MODEL LOG-LINIER G2 PADA OBSERVASI TRIVARIAT LENGKAP
The log-linear models are most used to catagorical data analysis. The catagorical scale is the function transformation value form forth scale measured of observation : nominal, ordinal, ratio and interval. For the data analysis to trivariates observation of categorical scale is focus to create the m...
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| Autor*in: |
I WAYAN SANTIYASA [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch ; Indonesisch |
| Erschienen: |
2012 |
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| Schlagwörter: |
Catagorical scale, Log-Linear Models, Goodness of fit, G2 Models. |
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| Übergeordnetes Werk: |
In: Jurnal Matematika - Universitas Udayana, 2016, (2012) |
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| Übergeordnetes Werk: |
year:2012 |
| Links: |
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| DOI / URN: |
10.24843/JMAT.2007.v01.i01.p03 |
|---|
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DOAJ006461948 |
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The log-linear models are most used to catagorical data analysis. The catagorical scale is the function transformation value form forth scale measured of observation : nominal, ordinal, ratio and interval. For the data analysis to trivariates observation of categorical scale is focus to create the models with proof for interaction the factor in the models to 2-factor or 3-factor with goodness-of-fit-test by G2 models. |
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The log-linear models are most used to catagorical data analysis. The catagorical scale is the function transformation value form forth scale measured of observation : nominal, ordinal, ratio and interval. For the data analysis to trivariates observation of categorical scale is focus to create the models with proof for interaction the factor in the models to 2-factor or 3-factor with goodness-of-fit-test by G2 models. |
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The log-linear models are most used to catagorical data analysis. The catagorical scale is the function transformation value form forth scale measured of observation : nominal, ordinal, ratio and interval. For the data analysis to trivariates observation of categorical scale is focus to create the models with proof for interaction the factor in the models to 2-factor or 3-factor with goodness-of-fit-test by G2 models. |
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