Annette Dobson (1990) "An Introduction to Generalized Linear Models". Page 9: Plant Weight Data.

ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
group <- gl(2, 10, 20, labels = c("Ctl","Trt"))
weight <- c(ctl, trt)
lm.D9 <- lm(weight ~ group) 
lm.D9

Call:
lm(formula = weight ~ group)

Coefficients:
(Intercept)     groupTrt  
      5.032       -0.371  

lm.D90 <- lm(weight ~ group - 1) # omitting intercept

anova(lm.D9)

	Df	Sum Sq	Mean Sq	F value	Pr(>F)
group	1	0.688205	0.688205	1.419101	0.2490232
Residuals	18	8.72925	0.4849583	NA	NA

summary(lm.D90)

Call:
lm(formula = weight ~ group - 1)

Residuals:
    Min      1Q  Median      3Q     Max 
-1.0710 -0.4938  0.0685  0.2462  1.3690 

Coefficients:
         Estimate Std. Error t value Pr(>|t|)    
groupCtl   5.0320     0.2202   22.85 9.55e-15 ***
groupTrt   4.6610     0.2202   21.16 3.62e-14 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.6964 on 18 degrees of freedom
Multiple R-squared:  0.9818,	Adjusted R-squared:  0.9798 
F-statistic: 485.1 on 2 and 18 DF,  p-value: < 2.2e-16

options(repr.plot.width=6, repr.plot.height=6)
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(lm.D9, las = 1)      # Residuals, Fitted, ...
par(opar)