# Teaching uncertainty

r
teaching
uncertainty
Author

Juan Tellez

``````library(tidyverse)
library(socviz)
theme_nice = function() {
theme_minimal(base_family = "Fira Sans") +
theme(panel.grid.minor = element_blank(),
plot.background = element_rect(fill = "white", color = NA),
plot.title = element_text(face = "bold"),
axis.title = element_text(face = "bold"),
strip.text = element_text(face = "bold", size = rel(0.8), hjust = 0),
strip.background = element_rect(fill = "grey80", color = NA),
legend.title = element_text(face = "bold"))
}

theme_set(theme_nice())``````

The way that I like to teach sampling uncertainty is to say: “imagine that we’d like to know how many kids the average American has, and that there are only 2,867 people in the US and they were all perfectly sampled in `{socviz::gss_sm}`.

How many kids does the average American have? In this mini-America world we can find the exact answer:

``````gss_sm %>%
summarise(`Average number of kids` = mean(childs, na.rm = TRUE)) %>%
knitr::kable(digits = 2, align = "c")``````
Average number of kids
1.85
``````tibble(reps = 1:500) %>%
mutate(samples = map(reps, ~ sample_n(starwars, size = 10, replace = FALSE))) %>%
unnest(samples) %>%
group_by(reps) %>%
summarise(mass = mean(mass, na.rm = TRUE))``````
``````# A tibble: 500 × 2
reps  mass
<int> <dbl>
1     1  72.5
2     2 103.
3     3  65.3
4     4  53.8
5     5  77
6     6  84.9
7     7  66.6
8     8  80.2
9     9 335.
10    10  70.4
# … with 490 more rows``````