# Why there are two p-values for the F value, one from Summary and others from ANOVA?

Consider the 'estandar' output of R that I copied from Anova from R output interpretation and added other variables.

Why there are two p-values? One from Summary F-statistic: 9.24 on 1 and 118 DF, p-value: 0.0001851 and others from ANOVA 6.241e-07***,0.08837,0.47480?

Residuals:
Min       1Q   Median       3Q      Max
-2.74004 -0.33827  0.04062  0.44064  1.22737

Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept)  2.11405    0.32089   6.588  1.3e-09 ***
V2           0.03883    0.01277   3.040  0.00292 **
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.6231 on 118 degrees of freedom
Multiple R-squared: 0.07262,    Adjusted R-squared: 0.06476
F-statistic:  9.24 on 1 and 118 DF,  p-value: 0.0001851

> anova(fit)
Analysis of Variance Table

Response: V1
Df Sum Sq Mean Sq F value   Pr(>F)
V2          1  3.588  3.5878  9.2402
6.241e-07***
V3          1  4       4       5.0889
0.08837
V4          1  3       3       5.7637
0.47480
....(here are more variables)
Residuals 118 45.818  0.3883
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1


6.241e-07***,0.08837,0.47480

F-statistic:  9.24 on 1 and 118 DF,  p-value: 0.0001851

• And the p-values are actually the same for linear regression with one predictor: x <- 1:5; y <- x^2; fit <- lm(y ~ x); summary(fit); anova(fit) – Roland Feb 13 at 8:41