This is a basic example which shows you how easy it is to generate
data with {TidyDensity}
:
library(TidyDensity)
library(dplyr)
library(ggplot2)
tidy_normal()
#> # A tibble: 50 × 7
#> sim_number x y dx dy p q
#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 -0.897 -3.00 0.000460 0.185 -0.897
#> 2 1 2 1.42 -2.87 0.00116 0.922 1.42
#> 3 1 3 -0.211 -2.75 0.00262 0.416 -0.211
#> 4 1 4 0.341 -2.63 0.00536 0.633 0.341
#> 5 1 5 0.664 -2.50 0.00993 0.747 0.664
#> 6 1 6 -1.19 -2.38 0.0167 0.117 -1.19
#> 7 1 7 1.10 -2.26 0.0257 0.864 1.10
#> 8 1 8 -0.374 -2.14 0.0364 0.354 -0.374
#> 9 1 9 -0.185 -2.01 0.0482 0.427 -0.185
#> 10 1 10 1.89 -1.89 0.0610 0.971 1.89
#> # ℹ 40 more rows
An example plot of the tidy_normal
data.
We can also take a look at the plots when the number of simulations is greater than nine. This will automatically turn off the legend as it will become too noisy.