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Set seed for bootsrap examples #123

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Sep 19, 2025
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Set seed for bootsrap examples #123

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12 changes: 12 additions & 0 deletions learn/statistics/infer/index.qmd
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Original file line number Diff line number Diff line change
Expand Up @@ -165,6 +165,8 @@ Continuing on with our example above, about the average number of hours worked a
#| label: "generate-point"
#| warning: false
#| message: false
set.seed(571)

gss %>%
specify(response = hours) %>%
hypothesize(null = "point", mu = 40) %>%
Expand All @@ -179,6 +181,8 @@ To generate a null distribution for the independence of two variables, we could
#| label: "generate-permute"
#| warning: false
#| message: false
set.seed(328)

gss %>%
specify(partyid ~ age) %>%
hypothesize(null = "independence") %>%
Expand All @@ -193,6 +197,8 @@ Depending on whether you're carrying out computation-based inference or theory-b
#| label: "calculate-point"
#| warning: false
#| message: false
set.seed(265)

gss %>%
specify(response = hours) %>%
hypothesize(null = "point", mu = 40) %>%
Expand All @@ -206,6 +212,8 @@ The output of `calculate()` here shows us the sample statistic (in this case, th
#| label: "specify-diff-in-means"
#| warning: false
#| message: false
set.seed(174)

gss %>%
specify(age ~ college) %>%
hypothesize(null = "independence") %>%
Expand All @@ -227,6 +235,8 @@ point_estimate <- gss %>%
calculate(stat = "mean")

# generate a null distribution
set.seed(693)

null_dist <- gss %>%
specify(response = hours) %>%
hypothesize(null = "point", mu = 40) %>%
Expand Down Expand Up @@ -301,6 +311,8 @@ Generally, to find a null distribution using theory-based methods, use the same
```{r}
#| message: false
#| warning: false
set.seed(533)

null_f_distn <- gss %>%
specify(age ~ partyid) %>%
hypothesize(null = "independence") %>%
Expand Down