Nothing
## -----------------------------------------------------------------------------
knitr::opts_chunk$set(fig.width = 6, fig.height = 4.5)
options(digits = 4)
## -----------------------------------------------------------------------------
library(ggplot2)
library(dplyr)
library(infer)
## -----------------------------------------------------------------------------
dplyr::glimpse(gss)
## -----------------------------------------------------------------------------
gss |>
ggplot2::ggplot() +
ggplot2::aes(x = partyid, y = age) +
ggplot2::geom_boxplot() +
ggplot2::scale_fill_brewer(type = "qual") +
ggplot2::theme(axis.text.x = ggplot2::element_text(angle = 45,
vjust = .5)) +
ggplot2::labs(x = "partyid: Political Party Affiliation",
y = "age: Age of Respondent")
## -----------------------------------------------------------------------------
# calculate the observed statistic
observed_f_statistic <- gss |>
specify(age ~ partyid) |>
hypothesize(null = "independence") |>
calculate(stat = "F")
## -----------------------------------------------------------------------------
# generate the null distribution using randomization
null_dist <- gss |>
specify(age ~ partyid) |>
hypothesize(null = "independence") |>
generate(reps = 1000, type = "permute") |>
calculate(stat = "F")
## -----------------------------------------------------------------------------
# visualize the null distribution and test statistic!
null_dist |>
visualize() +
shade_p_value(observed_f_statistic,
direction = "greater")
## -----------------------------------------------------------------------------
# visualize the theoretical null distribution and test statistic!
null_dist_theory <- gss |>
specify(age ~ partyid) |>
assume(distribution = "F")
visualize(null_dist_theory) +
shade_p_value(observed_f_statistic,
direction = "greater")
## -----------------------------------------------------------------------------
# visualize both null distributions and the test statistic!
null_dist |>
visualize(method = "both") +
shade_p_value(observed_f_statistic,
direction = "greater")
## -----------------------------------------------------------------------------
# calculate the p value from the observed statistic and null distribution
p_value <- null_dist |>
get_p_value(obs_stat = observed_f_statistic,
direction = "greater")
p_value
## -----------------------------------------------------------------------------
pf(observed_f_statistic$stat, 3, 496, lower.tail = FALSE)
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