Nothing
## ----settings, include=FALSE--------------------------------------------------
knitr::opts_chunk$set(fig.width = 6, fig.height = 4.5)
options(digits = 4)
## ----load-packages, echo = FALSE, message = FALSE, warning = FALSE------------
library(ggplot2)
library(dplyr)
library(infer)
## ----glimpse-gss-actual, warning = FALSE, message = FALSE---------------------
dplyr::glimpse(gss)
## ----plot-f, echo = FALSE-----------------------------------------------------
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")
## ----calc-obs-stat-f, warning = FALSE, message = FALSE------------------------
# calculate the observed statistic
observed_f_statistic <- gss %>%
specify(age ~ partyid) %>%
hypothesize(null = "independence") %>%
calculate(stat = "F")
## ----generate-null-f, warning = FALSE, message = FALSE------------------------
# generate the null distribution using randomization
null_dist <- gss %>%
specify(age ~ partyid) %>%
hypothesize(null = "independence") %>%
generate(reps = 1000, type = "permute") %>%
calculate(stat = "F")
## ----visualize-f, warning = FALSE, message = FALSE----------------------------
# visualize the null distribution and test statistic!
null_dist %>%
visualize() +
shade_p_value(observed_f_statistic,
direction = "greater")
## ----visualize-f-theor, warning = FALSE, message = FALSE----------------------
# 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-indep-both, warning = FALSE, message = FALSE-------------------
# visualize both null distributions and the test statistic!
null_dist %>%
visualize(method = "both") +
shade_p_value(observed_f_statistic,
direction = "greater")
## ----p-value-indep, warning = FALSE, message = FALSE--------------------------
# 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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