Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘’ 1 exp(coef) exp(-coef) lower .95 upper .95 sex 1.939 0.5157 1.153 3.26 Concordance= 0.59 (se = 0.034 ) Rsquare= 0.03 (max possible= 0.937 ) Likelihood ratio test= 6.15 on 1 df, p=0.01 Wald test = 6.2...
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘’ 1 #Tips:在公式里有一个lm()函数,它是一个线性模型函数(linear model),我们会在相关和回归里重点介绍它,这里只需要记住写法。同样,和t检验和wilcoxon检验一样这里,这里有“~”,而“~”之前的变量是数值变量,之后是分组变量。
(fit) Analysis of Variance Table Response: len Df R Sum Sq R Mean Sq Iter Pr(Prob) supp 1 205.35 205.35 5000 < 2e-16 *** dose 1 2224.30 2224.30 5000 < 2e-16 *** supp:dose 1 88.92 88.92 2276 0.04218 * Residuals 56 933.63 16.67 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ ...
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘’ 1 由于P<0.05,于是在α=0.05水平下,本例的回归系数有统计学意义,身高和年龄存在直线回归关系。 同理,对于上例中的回归方程,我们对模型进行回归系数的t检验,t检验的R代码如下: > summary(lm.reg) #回归系数的t检验 产生以下...
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘’ 1 由于P<0.05,于是在α=0.05水平下,本例的回归系数有统计学意义,身高和年龄存在直线回归关系。 同理,对于上例中的回归方程,我们对模型进行回归系数的t检验,t检验的R代...
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘’ 1 Residual standard error: 1.525 on 13 degrees of freedom Multiple R-squared: 0.991, Adjusted R-squared: 0.9903 F-statistic: 1433 on 1 and 13 DF, p-value: 1.091e-14 ...
# Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘’ 1 (标记显著性水平对应的符号) # # Residual standard error: 1.19 on 7 degrees of freedom(残差标准误与自由度) # Multiple R-squared: 0.6133, Adjusted R-squared: 0.558 (模型...
0.1870.85171shapeUniformity0.423090.267751.5800.11407maginalAdhesion0.292450.146901.9910.04650*singleEpithelialCellSize0.110530.179800.6150.53871bareNuclei0.335700.107153.1330.00173**blandChromatin0.423530.206732.0490.04049*normalNucleoli0.288880.139952.0640.03900*mitosis0.690570.398291.7340.08295.---Signif.codes:0‘...
一般情况，p值在0～0.001之间是非常非常显著，通常用‘***’号表示；在0.001～0.01之间是非常显著，通常用‘**’号表示；在0.01～0.05之间是比较显著，通常用‘**’号表示；在0.05～0.1之间是显著，通常用‘.’号表示；在0.1～1之间是不显著。我...
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘’ 1 Residual standard error: 0.3841 on 12 degrees of freedom Multiple R-squared: 0.9995, Adjusted R-squared: 0.9994 F-statistic: 1.139e+04 on 2 and 12 DF, p-value: < 2.2e-16 从F统计量和R方中可以看出,p值...