1 개요[ | ]
- R aov()
- "Fit An Analysis Of Variance Model → 분산분석 모델 피팅"
R
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MEM
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npk.aov <- aov(yield ~ block + N*P*K, npk)
npk.aov
Call: aov(formula = yield ~ block + N * P * K, data = npk) Terms: block N P K N:P N:K P:K Sum of Squares 343.2950 189.2817 8.4017 95.2017 21.2817 33.1350 0.4817 Deg. of Freedom 5 1 1 1 1 1 1 Residuals Sum of Squares 185.2867 Deg. of Freedom 12 Residual standard error: 3.929447 1 out of 13 effects not estimable Estimated effects may be unbalanced
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summary(npk.aov)
Df Sum Sq Mean Sq F value Pr(>F) block 5 343.3 68.66 4.447 0.01594 * N 1 189.3 189.28 12.259 0.00437 ** P 1 8.4 8.40 0.544 0.47490 K 1 95.2 95.20 6.166 0.02880 * N:P 1 21.3 21.28 1.378 0.26317 N:K 1 33.1 33.13 2.146 0.16865 P:K 1 0.5 0.48 0.031 0.86275 Residuals 12 185.3 15.44 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
2 같이 보기[ | ]
3 참고[ | ]
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