Package index • umncvmstats

Tests for Proportions

one_proportion_inference() wilson_test() binomial_test(): One-sample proportion inference

two_proportion_inference() pairwise_proportion_inference(): Two-sample proportion inference

paired_proportion_inference(): Paired proportion test (McNemar's)

independence_test(): Independence Tests for Count Data

Tests for Means

one_t_inference(): One-sample t-test

two_t_inference() pairwise_t_inference(): Two-sample t-test

paired_t_inference(): Paired t-test

two_t_power() two_t_power_equiv() two_t_power_me(): Power calculations for two sample t tests and confidence intervals

Nonparametric Inference

one_wilcoxon_inference(): One-sample Wilcoxon test

two_wilcoxon_inference() pairwise_wilcoxon_inference(): Two-sample Wilcoxon test

paired_wilcoxon_inference(): Paired Wilcoxon-test

kruskal_wallis_test(): Kruskal-Wallis test

Inference about Models

correlation_inference(): Correlation Tests and Confidence Intervals

model_anova(): Get model Anova table

model_coefs(): Get model coefficients

model_glance(): Get model summary information

model_means() pairwise_model_means() model_slopes() pairwise_model_slopes(): Get model means and slopes (trends)

model_predictions(): Get model predictions

diag_plots(): Display standard diagnostic plots for a model

Output

To control output from statistical tests

combine_tests() combine_tests_list(): Combine multiple tests together

as_gt(): Create a gt table object

tab_compact() tab_padding(): Compact a gt table

set_digits(): Set desired digits for values in an atest

format_signif(): Format to significant digits

format_pvalue() fmt_pvalue(): Format p-values

Misc

skim(): Summarize (skim) the variables in a data set

descriptive_statistics(): Compute descriptive statistics for a data set

new_assignment(): Create a blank new assignment

sample_data() sample_lm(): Create a random data set for regression

guess_cor(): Create a random scatterplot for guessing correlations

Graphics

geom_beeswarm() position_beeswarm(): Points, jittered to reduce overplotting using the beeswarm package

geom_bars(): Bar charts

scale_y_binary(): Make a binary scale

geom_smooth_logistic(): Add a smooth from a logistic regression

hide_y_axis(): Hide the y-axis of a ggplot

Datasets

mtcars2: Motor Trend Car Road Tests

passfail: Scores on pre/post test (generated data)