> seed.df <- read.table("seed.dat",header=T)
> seed.df
   seed root  y  n
1   O75 Bean 10 39
2   O75 Bean 23 62
3   O75 Bean 23 81
4   O75 Bean 26 51
5   O75 Bean 17 39
6   O75 Cmbr  5  6
7   O75 Cmbr 53 74
8   O75 Cmbr 55 72
9   O75 Cmbr 32 51
10  O75 Cmbr 46 79
11  O75 Cmbr 10 13
12  O73 Bean  8 16
13  O73 Bean 10 30
14  O73 Bean  8 28
15  O73 Bean 23 45
16  O73 Bean  0  4
17  O73 Cmbr  3 12
18  O73 Cmbr 22 41
19  O73 Cmbr 15 30
20  O73 Cmbr 32 51
21  O73 Cmbr  3  7
> attach(seed.df)

> #Binomial model with logit link
> seed.fit1 <- glm(cbind(y,n-y)~seed*root,binomial)
> summary(seed.fit1)

Coefficients:
                 Estimate Std. Error z value Pr(>|z|)  
(Intercept)       -0.4122     0.1842  -2.238   0.0252 *
seedO75           -0.1459     0.2232  -0.654   0.5132  
rootCmbr           0.5401     0.2498   2.162   0.0306 *
seedO75:rootCmbr   0.7781     0.3064   2.539   0.0111 *
---
(Dispersion parameter for binomial family taken to be 1)
    Null deviance: 98.719  on 20  degrees of freedom
Residual deviance: 33.278  on 17  degrees of freedom
>
> #Another way to fit the same model
> seed.fit2 <- glm(y/n~seed*root,binomial,weights=n)
> summary(seed.fit2)

Coefficients:
                 Estimate Std. Error z value Pr(>|z|)  
(Intercept)       -0.4122     0.1842  -2.238   0.0252 *
seedO75           -0.1459     0.2232  -0.654   0.5132  
rootCmbr           0.5401     0.2498   2.162   0.0306 *
seedO75:rootCmbr   0.7781     0.3064   2.539   0.0111 *
---
(Dispersion parameter for binomial family taken to be 1)
    Null deviance: 98.719  on 20  degrees of freedom
Residual deviance: 33.278  on 17  degrees of freedom
>

> #"Quasi-likelihood" fit - logit link
> seed.fit3 <- glm(y/n~seed*root,quasi(link="logit",variance="mu(1-mu)"),
+ weights=n)
> summary(seed.fit3)

Coefficients:
                 Estimate Std. Error t value Pr(>|t|)  
(Intercept)       -0.4122     0.2513  -1.640   0.1193  
seedO75           -0.1459     0.3045  -0.479   0.6379  
rootCmbr           0.5401     0.3409   1.584   0.1315  
seedO75:rootCmbr   0.7781     0.4181   1.861   0.0801 .
---
(Dispersion parameter for quasi family taken to be 1.861797)
    Null deviance: 98.719  on 20  degrees of freedom
Residual deviance: 33.278  on 17  degrees of freedom
>

> #"Quasi-likelihood" fit - identity link
> combo <- as.factor(c(rep("b75",5),rep("c75",6),rep("b73",5),rep("c73",5)))
> seed.fit4 <- glm(y/n~combo-1,quasi(link="identity",
+ variance="mu(1-mu)"),weights=n)
> summary(seed.fit4)

Coefficients:
         Estimate Std. Error t value Pr(>|t|)    
combob73  0.39837    0.06023   6.614 4.39e-06 ***
combob75  0.36397    0.03981   9.143 5.66e-08 ***
comboc73  0.53191    0.05734   9.277 4.60e-08 ***
comboc75  0.68136    0.03702  18.407 1.16e-12 ***
---
(Dispersion parameter for quasi family taken to be 1.861832)
    Null deviance:    Inf  on 21  degrees of freedom
Residual deviance: 33.278  on 17  degrees of freedom