library(AER)
library(MASS)
model_res <- lm(medv ~ lstat + I(crim + age), data = Boston)
RSSR <- sum(model_res$residuals^2)
model_unres <- lm(medv ~ lstat + crim + age, data = Boston)
USSR <- sum(model_unres$residuals^2)
# compute the F-statistic and assign it to `Fstat`
# compute the p-value and assign it to `pval`
# check whether the null is rejected at the 1% significance level
# verify your result with `linearHypothesis()`
# compute the F-statistic and assign it to `Fstat`
Fstat <- ((RSSR-USSR)/1)/(USSR/(nrow(Boston)-3-1))
# compute the p-value and assign it to `pval`
pval <- 1 - pf(Fstat, df1 = 1, df2 = nrow(Boston)-3-1)
# check whether the null is rejected at the 1% significance level
pval < 0.01
# verify your result with `linearHypothesis()`
linearHypothesis(model_unres, "age = crim")
test_object("Fstat")
test_object("pval")
test_or(test_output_contains("pval < 0.01"), test_output_contains("pval > 0.01"))
test_function_result("linearHypothesis")
success_msg("Correct! The null hypothesis is rejected at a 1% significance level.")