log_mod <- glm(formula = y ~ x1 + x2, data = dat, family = "binomial")
Perform a bootstrap to estimate these standard errors ourselves. It works as follows: i. Sample 2000 $(X_1,X_2,Y)$ triplets with replacement from your original data set of 2000 $(X_1,X_2,Y)$ triplets (the data set with groups A and B together). ii. Run a logistic regression of $Y$ on $X_1,X_2$ (including intercept), using the data constructed in from Step i. Store the coefficient vector. iii. Repeat Steps i and ii 100 times. You will have 100 coefficient vectors. Report the standard deviation of the intercept coefficients, and the $X_1$ coefficients, and the $X_2$ coefficients.