Test de corrélation et modèle de regression linéaire simple dans R/Rstudio HD

Le module 1 de la serie des modèles de regression linéaire dans Rstudio LINEAR REGRESSION MODELS IN R 1. Load and read data library(readxl) Database = read_excel("states.data.xlsx", col_names = TRUE, col_types = NULL, na="", sheet="states", skip = 0) 2. Simple linear regression 2.1 Examine the data before fitting models summary of expense and csat columns, all rows data.ex.csat = subset(Database, select = c("expense", "csat")) summary(data.ex.csat) correlation between expense and csat cor(data.ex.csat) 2.2 Plot the data before fitting models : scatter plot of expense vs csat plot(data.ex.csat) 2.3 Linear regression example Fit our regression model sat.mod1 = lm(csat ~ expense, data=Database) summary(sat.mod1) Regression csat vs percent data.per.csat = subset(Database, select = c("percent", "csat")) summary(data.per.csat) cor(data.per.csat) plot(data.per.csat) sat.mod2 = lm(csat ~ percent, data=Database) summary(sat.mod2) anova(sat.mod1, sat.mod2) AIC(sat.mod1, sat.mod2)