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測試數據幀:方差分析表的Interpeting R顯着性代碼?
> foo
x y z
1 0.191 0.324 0.620
2 0.229 0.302 0.648
3 0.191 0.351 0.626
4 0.229 0.324 0.630
5 0.152 0.374 0.656
6 0.191 0.295 0.609
7 0.229 0.267 0.665
8 0.152 0.353 0.657
9 0.152 0.355 0.655
兩個線性模型:
model1 <- lm(z~polym(x,y,degree = 1),data=foo)
model2 <- lm(z~polym(x,y,degree = 2),data=foo)
ANOVA兩個型號的回報:
> anova(model1,model2)
Analysis of Variance Table
Model 1: z ~ polym(x, y, degree = 1)
Model 2: z ~ polym(x, y, degree = 2)
Res.Df RSS Df Sum of Sq F Pr(>F)
1 6 0.002988
2 3 0.000169 3 0.00282 16.6 0.023 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
爲什麼單*
? 0.05> 0.023> 0.01,所以不應該打印.
符號?
表格代碼可能有點難以破譯,但:0.023在0.05(\ *)級別顯着,但不在0.01(\ * \ *)級別。 (。)字符對應於0.1或百分之十的級別。 – lmo
'0'***''/'0.001'**''/'0.01'*''/'0.05'。'' /'0.1'''/你的0.023落在0.01和0.05之間,因此它被標記爲一顆星。 – Jimbou