Introduction à la régression dans R
Richie Cotton
Data Evangelist at DataCamp
| species | mass_g |
|---|---|
| Brème commune | 242,0 |
| Perche | 5,9 |
| Brochet | 200,0 |
| Gardon | 40,0 |
| ... | ... |
library(ggplot2)
ggplot(fish, aes(mass_g)) +
geom_histogram(bins = 9) +
facet_wrap(vars(species))

fish %>%
group_by(species) %>%
summarize(mean_mass_g = mean(mass_g))
# A tibble: 4 x 2
species mean_mass_g
<chr> <dbl>
1 Bream 618.
2 Perch 382.
3 Pike 719.
4 Roach 152.
lm(mass_g ~ species, data = fish)
Call:
lm(formula = mass_g ~ species, data = fish)
Coefficients:
(Intercept) speciesPerch speciesPike speciesRoach
617.8 -235.6 100.9 -465.8
lm(mass_g ~ species + 0, data = fish)
Call:
lm(formula = mass_g ~ species + 0, data = fish)
Coefficients:
speciesBream speciesPerch speciesPike speciesRoach
617.8 382.2 718.7 152.0
Introduction à la régression dans R