Skip to contents

This function will generate n random points from a Gaussian distribution with a user provided, .mean, .sd - standard deviation and number of random simulations to be produced. The function returns a tibble with the simulation number column the x column which corresponds to the n randomly generated points, the dnorm, pnorm and qnorm data points as well.

The data is returned un-grouped.

The columns that are output are:

  • sim_number The current simulation number.

  • x The current value of n for the current simulation.

  • y The randomly generated data point.

  • dx The x value from the stats::density() function.

  • dy The y value from the stats::density() function.

  • p The values from the resulting p_ function of the distribution family.

  • q The values from the resulting q_ function of the distribution family.

Usage

tidy_normal(.n = 50, .mean = 0, .sd = 1, .num_sims = 1, .return_tibble = TRUE)

Arguments

.n

The number of randomly generated points you want.

.mean

The mean of the randomly generated data.

.sd

The standard deviation of the randomly generated data.

.num_sims

The number of randomly generated simulations you want.

.return_tibble

A logical value indicating whether to return the result as a tibble. Default is TRUE.

Value

A tibble of randomly generated data.

Details

This function uses the underlying stats::rnorm(), stats::pnorm(), and stats::qnorm() functions to generate data from the given parameters. For more information please see stats::rnorm()

Author

Steven P. Sanderson II, MPH

Examples

tidy_normal()
#> # A tibble: 50 × 7
#>    sim_number     x      y    dx       dy       p      q
#>    <fct>      <int>  <dbl> <dbl>    <dbl>   <dbl>  <dbl>
#>  1 1              1 -1.86  -4.13 0.000243 0.0313  -1.86 
#>  2 1              2 -1.29  -3.97 0.000638 0.0977  -1.29 
#>  3 1              3 -0.915 -3.81 0.00152  0.180   -0.915
#>  4 1              4 -2.67  -3.66 0.00329  0.00382 -2.67 
#>  5 1              5  0.465 -3.50 0.00651  0.679    0.465
#>  6 1              6  2.16  -3.34 0.0118   0.985    2.16 
#>  7 1              7  1.03  -3.18 0.0197   0.849    1.03 
#>  8 1              8 -0.129 -3.02 0.0306   0.449   -0.129
#>  9 1              9 -0.420 -2.86 0.0444   0.337   -0.420
#> 10 1             10 -1.53  -2.71 0.0609   0.0625  -1.53 
#> # ℹ 40 more rows