In-Class Activity 8 – Multiple Linear Regression

insurance <- read.csv(“insurance.csv”) head(insurance) colnames(insurance)

insurance\(bmi30 <- ifelse(insurance\)bmi >= 30, 1, 0)

insurance\(sex <- as.factor(insurance\)sex) insurance\(smoker <- as.factor(insurance\)smoker) insurance\(region <- as.factor(insurance\)region)

str(insurance)

mlr_model <- lm( expenses ~ age + children + bmi + bmi30 + sex + smoker + region, data = insurance )

summary(mlr_model)

caseA <- data.frame( age = 22, children = 3, bmi = 24, bmi30 = 0, sex = factor(“female”, levels = levels(insurance\(sex)), smoker = factor("no", levels = levels(insurance\)smoker)), region = factor(“northwest”, levels = levels(insurance$region)) )

caseB <- data.frame( age = 22, children = 1, bmi = 27, bmi30 = 0, sex = factor(“male”, levels = levels(insurance\(sex)), smoker = factor("yes", levels = levels(insurance\)smoker)), region = factor(“southeast”, levels = levels(insurance$region)) )

predA <- predict(mlr_model, newdata = caseA) predB <- predict(mlr_model, newdata = caseB)

predA predB