Returns distribution statistics in 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()
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