Operation Management Case/ Statistics

install.packages(MASS) library(MASS) data("Boston") summary(Boston) # Exploratory analysis # 1. Exploring the range and distribution hist(Boston$medv) hist(Boston$Cost) hist(Boston$Grad) hist(college$Debt) table(college$City) # 2. Exploring the association between Earnings and other numerical variables plot(Boston$medv ~ Boston$crim) cor(Boston$medv, Boston$crim) # 3. Exploring the association between Earnings and categorical variables tapply(college$Earnings, college$City, mean) boxplot(college$Earnings~college$City) # 4. Association between Earnings and Cost by City plot(college$Earnings~college$Cost, main="Scatterplot of Earnings against Cost", xlab = "Cost", ylab = "Earnings", pch=16, col=ifelse(college$City == 1, 20, 26)) legend("topright", legend=c("Other", "City"), pch=16, col=c(20, 26)) # Build models Model <- lm(Earnings ~ Cost + Grad + Debt + City, data = college) summary(Model) # Predict predict(Model, data.frame(Cost=25000, Grad=60, Debt=80, City=1)) predict(Model, data.frame(Cost=25000, Grad=60, Debt=80, City=1), level = 0.95, interval = "confidence") predict(Model, data.frame(Cost=25000, Grad=60, Debt=80, City=1), level = 0.95, interval = "prediction") # Model selection: goodness-of-fit measure Model1 <- lm(Earnings ~ Cost, data = college) Model2 <- lm(Earnings ~ Cost + Grad + Debt, data = college) summary(Model1) summary(Model2) Model3 <- lm(Earnings ~ Cost + Grad + Debt + City, data = college) summary(Model3) round(summary(Model3)$coefficients, digits = 4) # Lab 7 Q 15 library(readxl) myData <- read_excel("Labs/Ch7_Q15_V18_Data_File.xlsx") View(myData) model <- lm(Price ~ Sqft + Beds + Baths + Colonial, data = myData) summary(model) predict(model, data.frame(Sqft=2500, Beds=3, Baths=2, Colonial=1), level=0.95, interval="prediction") # Lab 7 Q 22 library(readxl) myData <- read_excel("Labs/Ch7_Q22_V11_Data_File.xlsx") View(myData) summary(myData) model <- lm(Property_Taxes ~ Size, data = myData) summary(model) # Lab 7 Q 33 library(readxl) myData <- read_excel("Labs/Ch7_Q33_V07_Data_File.xlsx") View(myData) summary(myData) model <- lm(Time ~ Miles + Load + Speed + Oil, data = myData) summary(model)