# set seed for reproducibility set.seed(3) # set number of sampling iterations N <- # initialize `beta_hats` beta_hats <- # conduct the simulation using `for()` for(i in 1:N) { } # compare the mean of estimates to the true parameter # set seed for reproducibility set.seed(3) # set number of sampling iterations N <- 1000 # initialize vector `beta_hats` beta_hats <- c() # loop estimation for (i in 1:N) { # simulate the dataset X <- runif(100, -5, 5) Y <- X^2 + rnorm(100) # estimate the linear regression function ms_mod <- lm(Y ~ X) # save the estimate beta_hats[i] <- ms_mod$coefficients[1] } # compare mean of estimates and the true parameter mean(beta_hats) == 0 test_object("beta_hats") test_student_typed("==")