> data(chickwts)

> chickwts[c(1:3, 69:71), ]
   weight      feed
1     179 horsebean
2     160 horsebean
3     136 horsebean
69    222    casein
70    283    casein
71    332    casein

> a = aov(weight ~ feed, data = chickwts)

> summary(a)
            Df Sum Sq Mean Sq F value    Pr(>F)    
feed         5 231129   46226  15.365 5.936e-10 ***
Residuals   65 195556    3009                      
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

> l = lm(weight ~ feed, data = chickwts)

> summary(l)

Call:
lm(formula = weight ~ feed, data = chickwts)

Residuals:
     Min       1Q   Median       3Q      Max 
-123.909  -34.413    1.571   38.170  103.091 

Coefficients:
              Estimate Std. Error t value Pr(>|t|)    
(Intercept)    323.583     15.834  20.436  < 2e-16 ***
feedhorsebean -163.383     23.485  -6.957 2.07e-09 ***
feedlinseed   -104.833     22.393  -4.682 1.49e-05 ***
feedmeatmeal   -46.674     22.896  -2.039 0.045567 *  
feedsoybean    -77.155     21.578  -3.576 0.000665 ***
feedsunflower    5.333     22.393   0.238 0.812495    
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 

Residual standard error: 54.85 on 65 degrees of freedom
Multiple R-Squared: 0.5417,	Adjusted R-squared: 0.5064 
F-statistic: 15.36 on 5 and 65 DF,  p-value: 5.936e-10 


> anova(l)
Analysis of Variance Table

Response: weight
          Df Sum Sq Mean Sq F value    Pr(>F)    
feed       5 231129   46226  15.365 5.936e-10 ***
Residuals 65 195556    3009                      
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1