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This function returns a summary statistics tibble. It will use the y column from the tidy_ distribution function.

Usage

tidy_distribution_summary_tbl(.data, ...)

Arguments

.data

The data that is going to be passed from a a tidy_ distribution function.

...

This is the grouping variable that gets passed to dplyr::group_by() and dplyr::select().

Value

A summary stats tibble

Details

This function takes in a tidy_ distribution table and will return a tibble of the following information:

  • sim_number

  • mean_val

  • median_val

  • std_val

  • min_val

  • max_val

  • skewness

  • kurtosis

  • range

  • iqr

  • variance

  • ci_hi

  • ci_lo

The kurtosis and skewness come from the package healthyR.ai

Author

Steven P. Sanderson II, MPH

Examples

library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

tn <- tidy_normal(.num_sims = 5)
tb <- tidy_beta(.num_sims = 5)

tidy_distribution_summary_tbl(tn)
#> # A tibble: 1 × 12
#>   mean_val median_val std_val min_val max_val skewness kurtosis range   iqr
#>      <dbl>      <dbl>   <dbl>   <dbl>   <dbl>    <dbl>    <dbl> <dbl> <dbl>
#> 1   -0.106    -0.0414   0.936   -2.71    3.09   0.0808     3.01  5.81  1.35
#> # ℹ 3 more variables: variance <dbl>, ci_low <dbl>, ci_high <dbl>
tidy_distribution_summary_tbl(tn, sim_number)
#> # A tibble: 5 × 13
#>   sim_number mean_val median_val std_val min_val max_val skewness kurtosis range
#>   <fct>         <dbl>      <dbl>   <dbl>   <dbl>   <dbl>    <dbl>    <dbl> <dbl>
#> 1 1           -0.158     -0.0498   0.838   -2.51    1.57  -0.224      2.85  4.08
#> 2 2           -0.248     -0.284    1.05    -2.71    2.39  -0.0132     3.02  5.11
#> 3 3            0.0799     0.170    0.889   -1.71    2.22   0.0760     2.57  3.93
#> 4 4           -0.233     -0.352    0.945   -1.89    3.09   0.844      4.55  4.99
#> 5 5            0.0309     0.104    0.932   -1.67    1.71  -0.194      1.98  3.39
#> # ℹ 4 more variables: iqr <dbl>, variance <dbl>, ci_low <dbl>, ci_high <dbl>

data_tbl <- tidy_combine_distributions(tn, tb)

tidy_distribution_summary_tbl(data_tbl)
#> # A tibble: 1 × 12
#>   mean_val median_val std_val min_val max_val skewness kurtosis range   iqr
#>      <dbl>      <dbl>   <dbl>   <dbl>   <dbl>    <dbl>    <dbl> <dbl> <dbl>
#> 1    0.182      0.330   0.749   -2.71    3.09   -0.732     4.33  5.81 0.693
#> # ℹ 3 more variables: variance <dbl>, ci_low <dbl>, ci_high <dbl>
tidy_distribution_summary_tbl(data_tbl, dist_type)
#> # A tibble: 2 × 13
#>   dist_type  mean_val median_val std_val min_val max_val skewness kurtosis range
#>   <fct>         <dbl>      <dbl>   <dbl>   <dbl>   <dbl>    <dbl>    <dbl> <dbl>
#> 1 Gaussian …   -0.106    -0.0414   0.936 -2.71     3.09    0.0808     3.01 5.81 
#> 2 Beta c(1,…    0.470     0.464    0.287  0.0109   0.997   0.118      1.82 0.986
#> # ℹ 4 more variables: iqr <dbl>, variance <dbl>, ci_low <dbl>, ci_high <dbl>