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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)

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.

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 -0.912  -3.60 0.000267 0.181  -0.912 
#>  2 1              2  0.432  -3.47 0.000706 0.667   0.432 
#>  3 1              3  0.0670 -3.33 0.00168  0.527   0.0670
#>  4 1              4 -1.73   -3.20 0.00361  0.0421 -1.73  
#>  5 1              5  0.512  -3.07 0.00698  0.696   0.512 
#>  6 1              6 -0.645  -2.93 0.0122   0.259  -0.645 
#>  7 1              7  0.275  -2.80 0.0195   0.608   0.275 
#>  8 1              8  0.0211 -2.66 0.0283   0.508   0.0211
#>  9 1              9  0.703  -2.53 0.0378   0.759   0.703 
#> 10 1             10 -0.581  -2.39 0.0472   0.281  -0.581 
#> # ℹ 40 more rows