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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)
#> Warning: package 'dplyr' was built under R version 4.2.3
#> 
#> 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  -0.0647   -0.00657    1.03   -3.47    2.74   -0.213     2.93  6.21  1.37
#> # 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           -0.187     -0.294    1.08    -2.16    2.74   0.409      2.61  4.90
#> 2 2           -0.171     -0.171    0.918   -2.67    2.03  -0.0572     3.38  4.71
#> 3 3           -0.101      0.0363   1.06    -2.68    1.54  -0.652      2.84  4.22
#> 4 4            0.0619    -0.0397   1.03    -1.97    1.82  -0.142      1.98  3.79
#> 5 5            0.0737     0.155    1.05    -3.47    2.05  -0.663      4.38  5.53
#> # 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    0.218      0.356   0.806   -3.47    2.74    -1.00     4.83  6.21 0.730
#> # 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…  -0.0647   -0.00657   1.03  -3.47      2.74  -0.213       2.93 6.21 
#> 2 Beta c(1…   0.500     0.509     0.296  0.00622   0.999 -0.00510     1.83 0.992
#> # ℹ 4 more variables: iqr <dbl>, variance <dbl>, ci_low <dbl>, ci_high <dbl>