due to the relationship between the

due to the relationship between the instrument
signal, y, and the analyte concentration, x. The second is the random experimental
error in the y-values, which is called the variation about regression. As we have
seen in Chapter 3, ANOVA is a powerful method for separating two sources of variation
is such situations. In regression problems, the average of the y-values of the calibration
points, , is important in defining these sources of variation. Individual values
of yi differ from for the two reasons given above. ANOVA is applied to separating the
two sources of variation by using the relationship that the total sum of squares (SS)
about is equal to the SS due to regression plus the SS about regression:

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Hasil (Bahasa Indonesia) 1: [Salinan]

Disalin!

due to the relationship between the instrumentsignal, y, and the analyte concentration, x. The second is the random experimentalerror in the y-values, which is called the variation about regression. As we haveseen in Chapter 3, ANOVA is a powerful method for separating two sources of variationis such situations. In regression problems, the average of the y-values of the calibrationpoints, , is important in defining these sources of variation. Individual valuesof yi differ from for the two reasons given above. ANOVA is applied to separating thetwo sources of variation by using the relationship that the total sum of squares (SS)about is equal to the SS due to regression plus the SS about regression:

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Hasil (Bahasa Indonesia) 2:[Salinan]

Disalin!

karena hubungan antara instrumen
sinyal, y, dan konsentrasi analit, x. Yang kedua adalah eksperimental acak
kesalahan dalam y-nilai, yang disebut variasi tentang regresi. Seperti yang telah kita
lihat dalam Bab 3, ANOVA adalah metode yang kuat untuk memisahkan dua sumber variasi
adalah situasi seperti itu. Dalam masalah regresi, rata-rata dari y-nilai kalibrasi
poin,, adalah penting dalam menentukan sumber-sumber variasi. Nilai-nilai individu
dari yi berbeda untuk dua alasan yang diberikan di atas. ANOVA diterapkan untuk memisahkan
dua sumber variasi dengan menggunakan hubungan bahwa total jumlah kotak (SS)
sekitar sama dengan SS karena regresi ditambah SS tentang regresi:

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Hasil (Bahasa Indonesia) 3:[Salinan]

Disalin!

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