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 0.332 -3.64 0.000240 0.630 0.332
#> 2 1 2 0.307 -3.51 0.000650 0.621 0.307
#> 3 1 3 -0.927 -3.37 0.00156 0.177 -0.927
#> 4 1 4 0.841 -3.24 0.00333 0.800 0.841
#> 5 1 5 0.785 -3.11 0.00631 0.784 0.785
#> 6 1 6 1.76 -2.97 0.0107 0.961 1.76
#> 7 1 7 0.859 -2.84 0.0161 0.805 0.859
#> 8 1 8 0.560 -2.71 0.0221 0.712 0.560
#> 9 1 9 -1.03 -2.57 0.0279 0.151 -1.03
#> 10 1 10 0.740 -2.44 0.0329 0.770 0.740
#> # 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.