install.packages("tidyverse")
install.packages("tidymodels")
install.packages("fivethirtyeight")Installation des packages
Chargement des packages
library(tidyverse)
library(tidymodels)
library(fivethirtyeight)Preparation des donnees
Renommer les colonnes RottenTomatoes comme “critics” et “audience”
Renommer le jeu de donnees comme “movie_scores”
movie_scores<-fandango|>
rename(
critics=rottentomatoes,
audience=rottentomatoes_user
)Apercu des donnees
movie_scores|>
select(critics, audience)# A tibble: 146 × 2
critics audience
<int> <int>
1 74 86
2 85 80
3 80 90
4 18 84
5 14 28
6 63 62
7 42 53
8 86 64
9 99 82
10 89 87
# ℹ 136 more rows
Visualisation des donnees
ggplot(movie_scores, aes(x=critics, y=audience))+
geom_point()Ajustement du modele
movie_fit<-linear_reg()|>
fit(audience~critics, data=movie_scores)
tidy(movie_fit)# A tibble: 2 × 5
term estimate std.error statistic p.value
<chr> <dbl> <dbl> <dbl> <dbl>
1 (Intercept) 32.3 2.34 13.8 4.03e-28
2 critics 0.519 0.0345 15.0 2.70e-31