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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  1.43   -3.98 0.000213 0.923    1.43  
#>  2 1              2  0.662  -3.83 0.000592 0.746    0.662 
#>  3 1              3  0.280  -3.68 0.00144  0.610    0.280 
#>  4 1              4 -0.893  -3.52 0.00308  0.186   -0.893 
#>  5 1              5 -1.69   -3.37 0.00579  0.0457  -1.69  
#>  6 1              6 -2.72   -3.22 0.00961  0.00329 -2.72  
#>  7 1              7 -1.66   -3.06 0.0142   0.0487  -1.66  
#>  8 1              8 -0.897  -2.91 0.0188   0.185   -0.897 
#>  9 1              9  0.0596 -2.76 0.0230   0.524    0.0596
#> 10 1             10  1.06   -2.61 0.0271   0.856    1.06  
#> # … with 40 more rows