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Distribution Statistics

Source: R/stats-binomial-tbl.R
util_binomial_stats_tbl.Rd

Returns distribution statistics in a tibble.

Usage

util_binomial_stats_tbl(.data)

Arguments

.data

The data being passed from a tidy_ distribution function.

Value

A tibble

Details

This function will take in a tibble and returns the statistics of the given type of tidy_ distribution. It is required that data be passed from a tidy_ distribution function.

See also

Other Binomial: tidy_binomial(), tidy_negative_binomial(), tidy_zero_truncated_binomial(), tidy_zero_truncated_negative_binomial(), util_binomial_param_estimate(), util_negative_binomial_param_estimate(), util_zero_truncated_binomial_param_estimate(), util_zero_truncated_binomial_stats_tbl(), util_zero_truncated_negative_binomial_param_estimate(), util_zero_truncated_negative_binomial_stats_tbl()

Other Distribution Statistics: util_bernoulli_stats_tbl(), util_beta_stats_tbl(), util_burr_stats_tbl(), util_cauchy_stats_tbl(), util_chisquare_stats_tbl(), util_exponential_stats_tbl(), util_f_stats_tbl(), util_gamma_stats_tbl(), util_generalized_beta_stats_tbl(), util_generalized_pareto_stats_tbl(), util_geometric_stats_tbl(), util_hypergeometric_stats_tbl(), util_inverse_burr_stats_tbl(), util_inverse_pareto_stats_tbl(), util_inverse_weibull_stats_tbl(), util_logistic_stats_tbl(), util_lognormal_stats_tbl(), util_negative_binomial_stats_tbl(), util_normal_stats_tbl(), util_paralogistic_stats_tbl(), util_pareto1_stats_tbl(), util_pareto_stats_tbl(), util_poisson_stats_tbl(), util_t_stats_tbl(), util_triangular_stats_tbl(), util_uniform_stats_tbl(), util_weibull_stats_tbl(), util_zero_truncated_binomial_stats_tbl(), util_zero_truncated_geometric_stats_tbl(), util_zero_truncated_negative_binomial_stats_tbl(), util_zero_truncated_poisson_stats_tbl()

Author

Steven P. Sanderson II, MPH

Examples

library(dplyr)

tidy_binomial() |>
  util_binomial_stats_tbl() |>
  glimpse()
#> Rows: 1
#> Columns: 18
#> $ tidy_function     <chr> "tidy_binomial"
#> $ function_call     <chr> "Binomial c(0, 1)"
#> $ distribution      <chr> "Binomial"
#> $ distribution_type <chr> "discrete"
#> $ points            <dbl> 50
#> $ simulations       <dbl> 1
#> $ mean              <dbl> 0
#> $ mode_lower        <dbl> 0
#> $ mode_upper        <dbl> 1
#> $ range             <chr> "0 to 0"
#> $ std_dv            <dbl> 0
#> $ coeff_var         <dbl> NaN
#> $ skewness          <dbl> -Inf
#> $ kurtosis          <dbl> NaN
#> $ computed_std_skew <dbl> NaN
#> $ computed_std_kurt <dbl> NaN
#> $ ci_lo             <dbl> 0
#> $ ci_hi             <dbl> 0