plots with statistics

library(ggstatsplot)
library(ggplot2)
library(dplyr)
library(PMCMRplus)
movies_long<-movies_long

movies_long %>% ggbetweenstats(x=mpaa,y=rating)

movies_long %>% ggbetweenstats(x=mpaa,y=rating,type="r", outlier.tagging=TRUE, outlier.label=title)

Warning: ggrepel: 15 unlabeled data points (too many overlaps). Consider increasing max.overlaps

library(afex)

Loading required package: lme4
Loading required package: Matrix
************
Welcome to afex. For support visit: http://afex.singmann.science/
- Functions for ANOVAs: aov_car(), aov_ez(), and aov_4()
- Methods for calculating p-values with mixed(): 'S', 'KR', 'LRT', and 'PB'
- 'afex_aov' and 'mixed' objects can be passed to emmeans() for follow-up tests
- NEWS: emmeans() for ANOVA models now uses model = 'multivariate' as default.
- Get and set global package options with: afex_options()
- Set orthogonal sum-to-zero contrasts globally: set_sum_contrasts()
- For example analyses see: browseVignettes("afex")
************

Attaching package: ‘afex’

The following object is masked from ‘package:lme4’:

    lmer

ggwithinstats(data=WRS2::WineTasting, x=Wine, y=Taste)

ggdotplotstats(
  data = movies_long,
  x = budget,
  y = genre,
  test.value = 30
)

library(ggside)

Registered S3 method overwritten by 'ggside':
  method from   
  +.gg   ggplot2

ggscatterstats(
  data = movies_long,
  x = budget,
  y = rating
)

`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

ggscatterstats(
  data = movies_long,
  x = budget,
  y = rating,
  type = "r",
  label.var = title,
  label.expression = budget > 150
  & rating > 7.5
)

`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
`stat_bin()` using `bins = 30`. Pick better value with `binwidth`.

library(ggcorrplot)
ggcorrmat(dplyr::starwars)

ggpiestats(
  data = dplyr::filter(
    movies_long,
    genre %in% c("Drama", "Comedy")
  ),
  x = mpaa,
  y = genre
)

ggpiestats(
  data = dplyr::filter(
    movies_long,
    genre %in% c("Drama", "Comedy")
  ),
  x = mpaa,
  y = genre,
  label="both"
)

# model
mod <- lm(
  formula = rating ~ mpaa,
  data = movies_long
)
# plot
ggcoefstats(mod)

#reference: https://github.com/IndrajeetPatil/ggstatsplot