df <- data.frame(
  trials=c(5, 8, 10, 3, 4),
  successes=c(2, 7, 1, 2, 3),
  x=c(0.8, 3.2, 0.2, 1.0, 1.3),
  flag=c(0, 1, 1, 1, 0)
)

summary( glm(cbind(successes, trials-successes) ~ x + flag, family=binomial, data=df) )

Call:
glm(formula = cbind(successes, trials - successes) ~ x + flag, family = binomial,
    data = df)

Deviance Residuals:
      1        2        3        4        5
-0.3732  -0.3753  -0.5558   1.0811   0.4464

Coefficients:
            Estimate Std. Error z value Pr(>|z|)
(Intercept)  -1.1402     0.8477  -1.345   0.1786
x             1.3404     0.5005   2.678   0.0074 **
flag         -0.7803     0.9165  -0.851   0.3946
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

(Dispersion parameter for binomial family taken to be 1)

    Null deviance: 14.011  on 4  degrees of freedom
Residual deviance:  1.957  on 2  degrees of freedom
AIC: 17.196

Number of Fisher Scoring iterations: 4