Package index • stests

All functions
`ci_p()`	Confidence intervals for Binomial proportions
`ci_p_add_4()`	Add-4 Wald-t Confidence Interval for Binomial Proportion
`ci_p_agresti_coull()`	Agresti-Coull confidence interval for Binomial proportion
`ci_p_arcsine()`	ArcoSeno confidence interval for Binomial proportion
`ci_p_arcsine_ac()`	Arcsine Wald Confidence Interval with Continuity Correction Anscombe for Binomial Proportion
`ci_p_arcsine_cc()`	Arcsine Wald Confidence Interval with Continuity Correction for Binomial Proportion
`ci_p_clopper_pearson()`	Clopper-Pearson confidence interval for Binomial proportion
`ci_p_coverage()`	Coverage for interval confidence p
`ci_p_coverage_plot()`	Coverage for interval confidence p
`ci_p_hpd_jeffreys()`	Highest Posterior Density (HPD) interval for Binomial proportion using Jeffreys prior
`ci_p_jeffreys()`	Bayesian confidence interval for Binomial proportion using Jeffreys prior (non-informative prior).
`ci_p_rindskopf()`	Rindskopf confidence interval for Binomial proportion
`ci_p_wald()`	Wald confidence interval for Binomial proportion
`ci_p_wilson()`	Wilson confidence interval for Binomial proportion
`d.meantest()`	D-value for hypothesis test using vectors
`d_meantest()`	D-value for hypothesis test using values
`mult_var_matrices_test()`	Tests for homogeneity of covariances matrices
`one_covar_matrix_test()`	Test for \(\Sigma\) in a \(Np(\mu, \Sigma)\)
`one_mean_vector_test()`	Test for \(\mu\) in a \(Np(\mu, \Sigma)\)
`plot(<htest>)`	To plot p-value area
`shade.dist()`	Shade for continuous distributions
`shade.norm()` `shade.t()` `shade.F()` `shade.chi()`	Shading functions for interpretation of pdf probabilities
`two_mean_vector_test()`	Tests for Equality of Two Normal Mean Vectors
`t_test()`	Student's t-Test using values
`var.test()`	Variance test using vectors
`var_test()`	Variance test using values
`z.test()`	Mean test using vector
`z_test()`	Mean test using values

Reference

All functions