Intermediary Regression in R
Richie Cotton
Data Evangelist at DataCamp
Het effect van lengte op de verwachte massa verschilt per soort.
Het effect van één verklarende variabele op de verwachte respons verandert afhankelijk van de waarde van een andere verklarende variabele.
response ~ explntry1 + explntry2
response_var ~ explntry1 * explntry2
response ~ explntry1 + explntry2 + explntry1:explntry2
mass_g ~ length_cm + species
mass_g ~ length_cm * species
mass_g ~ length_cm + species + length_cm:species
lm(mass_g ~ length_cm * species, data = fish)
Call:
lm(formula = mass_g ~ length_cm * species, data = fish)
Coefficients:
(Intercept) length_cm speciesPerch speciesPike
-1035.348 54.550 416.172 -505.477
speciesRoach length_cm:speciesPerch length_cm:speciesPike length_cm:speciesRoach
705.971 -15.639 -1.355 -31.231
mdl_inter <- lm(mass_g ~ species + species:length_cm + 0, data = fish)
Call:
lm(formula = mass_g ~ species + species:length_cm + 0, data = fish)
Coefficients:
speciesBream speciesPerch speciesPike speciesRoach
-1035.35 -619.18 -1540.82 -329.38
speciesBream:length_cm speciesPerch:length_cm speciesPike:length_cm speciesRoach:length_cm
54.55 38.91 53.19 23.32
speciesBream speciesPerch speciesPike speciesRoach
-1035.35 -619.18 -1540.82 -329.38
speciesBream:length_cm speciesPerch:length_cm speciesPike:length_cm speciesRoach:length_cm
54.55 38.91 53.19 23.32
coefficients(mdl_bream)
(Intercept) length_cm
-1035.34757 54.54998
Intermediary Regression in R