R Markdown

sum(y^2)

view(Auto)

horsepower_num <- as.numeric(horspower)

horsepower_num <- as.numeric(horsepower)

library(readr)

Auto <- read_csv(“Auto.csv”)

View(Auto)

pairs(Auto)

pairs(mpg,origin,year,acceleration,weight,displacement,cylind ers)

attach(mpg)

pairs(Auto$mpg)

pairs(Auto\(mpg,Auto\)origin,Auto\(year,Auto\)acceleration,Auto\(w eight, Auto\)displacement)

attach(year)

attach(Auto)

?Auto

??Auto

view(Auto)

view(auto)

View(Auto)

pairs(Auto)

pairs(Auto\(mpg, Auto\)cylinders, Auto\(displacement, Auto\)weight)

fix(Auto)

Auto=na.omit(Auto)

attach(Auto)

pairs(Auto\(mpg, Auto\)cylinders)

view(Auto$mpg)

cylinders=as.factor(Cylinders)

cylinders=as.factor(Auto$cylinders)

pairs(Auto\(mpg, Auto\)cylinders)

mpg=as.factor(mpg)

pairs(Auto\(mpg, Auto\)cylinders)

plot(Auto$mpg)

plot(Auto\(mpg, Auto\)cylinders)

pairs(~ Auto\(mpg + Auto\)cylinders)

horsepower=as.factor(horsepower)

pairs(~ Auto\(mpg +Auto\)cylinders +Auto$horsepower)

pairs(~ Auto\(mpg + Auto\)cylinders + Auto$horsepower)

horsepower=as.factor(horsepower)

pairs(~Auto\(mpg + Auto\)horsepower, Auto) pairs(~Auto\(mpg + Auto\)horsepower)

Auto=na.omit(Auto)

dim(Auto)

NewAuto=na.omit(Auto)

View(NewAuto)

View(NewAuto)

str(Auto)

complete.cases(Auto)

Auto <- Auto[completed.cas]

Auto <- Auto[completed.cases(Auto),]

x <- Auto[complete.cases(Auto),]

str(x)

na.strings=‘?’

Auto\(x <- gsub("?",NA,Auto\)x, fixed = TRUE)

is.na(Auto)

Auto=read.csv(Auto, header=TRUE, na.strings = ‘?’, fill=TRUE)

Auto=read.csv(“Auto.csv”,header=T,na.strings =“?”) Auto=read.csv(“Auto.csv”,header=T,na.strings =“?”)

fix(Auto)

dim(Auto)

na.omit(Auto)

dim(Auto)

view(Auto)

Auto=na.omit(Auto)

fix(Auto)

dim(Auto)

view(Auto)

pairs(Auto)

pairs(~ Auto\(mpg + Auto\)cylinders + Auto\(horsepower + Auto\)weight + Auto\(acceleration + Auto\)origin + Auto\(year + Auto\)displacement)

cor( Auto\(mpg + Auto\)cylinders + Auto\(horsepower + Auto\)weight + Auto\(acceleration + Auto\)origin + Auto\(year + Auto\)displacement)

cor(Auto\(mpg, Auto\)cylinders, Auto\(horsepower, Auto\)weight, Auto\(acceleration, Auto\)origin, Auto\(year, Auto\)displacement)

cor(Auto\(mpg, Auto\)cylinders)

cor(Auto\(mpg, Auto\)displacement)

cor(Auto\(mpg, Auto\)horsepower)

Auto.cor = cor(Auto)

res <- cor.test(Auto\(mpg, Auto\)cylinders, Auto$displacement)

cor(x, use= “num”)

NoNameAuto <- select(Auto\(mpg, Auto\)cylinders, Auto\(displacement,Auto\)horsepower, Auto\(weight, Auto\)acceleration, Auto\(origin, Auto\)year)

head(NoNameAuto)

library(ISLR)

library(ISLR)

view(Auto)

NoNameAuto <- select(Auto\(mpg, Auto\)cylinders, Auto\(displacement,Auto\)horsepower, Auto\(weight, Auto\)acceleration, Auto\(origin, Auto\)year)

require(ggpubr)

require(tidyverse)

require(Hmisc)

require(corrplot)

cor(Auto[,unlist(lapply(Auto, is.numeric))])

lm.fit=lm(Auto\(mpg∼Auto\)cylinders+Auto\(displacement+Auto\)hors epower+Auto\(weight+Auto\)weight+Auto\(acceleration+Auto\)year+Au to$origin ,data=Auto )

summary (lm.fit)

lm.fit=lm(Auto\(mpg∼Auto\)cylinders+Auto\(displacement+Auto\)hors epower+Auto\(weight+Auto\)weight+Auto\(acceleration+Auto\)year+Au to$origin ,data=Auto ) summary (lm.fit)

lm.fit=lm(Auto\(mpg ~ Auto\)cylinders+Auto\(displacement+Auto\)horsepower+Auto\(weight+ Auto\)weight+Auto\(acceleration+Auto\)year+Auto$origin ,data=Auto )

summary(lm.fit)

summary(lm.fit)

plot(lm.fit)

plot(lm.fit)

plot(lm.fit)

summary (lm(medv∼lstat*mpg ,data=Auto))

summary (lm(medv∼lstat*mpg ,data=Auto))

lm.fit=lm(medv∼lstat , data=Auto)

attach(Auto)

lm.fit=lm(medv∼lstat)

lm.fit=lm(medv~lstat , data=Auto)

attach(Auto)

lm.fit=lm(medv~lstat)

lm.fit

lstat

lm.fit=lm(medv∼lstat , data=Auto)

attach(Auto)

view(Auto)

View(Auto)

lm.fit=lm(medv∼lstat , data=Auto)

lm.fit=lm(medv∼lstat , data=Auto.csv)

lm.fit=lm(medv~lstat , data=Auto)

library(readr)

Auto <- read_csv(“Auto.csv”)

View(Auto)

summary(lm.fit)

summary(lm.fit)

Auto=read.csv(“Auto.csv”,header=T,na.strings =“?”)

fix(Auto)

dim(Auto)

na.omit(Auto)

dim(Auto)

view(Auto)

Auto=na.omit(Auto)

fix(Auto)

dim(Auto)

view(Auto)

install.packages(“ISLR”)

Rdata <- readRDS(“~/R/win-library/4.0/ISLR/data/Rdata.rds”)

view(carseats)

data(carseats)

attach(carseats)

attach(Carseats)

library(ISLR)

force(Carseats)

attach(Carseats)

lm.fit=lm(medv∼lstat)

lm.fit=lm(medv~lstat)

lm.fit=lm(medv~lstat)

lm.fit=lm(medv~lstat , data=Carseats

attach(Carseats)

lm.fit=lm(medv~lstat)

lm.fit=lm(medv~lstat, data=Carseats)

attach (Carseats)

lm.fit=lm(medv~lstat)

View(Carseats)

fit2=lm(medv~.,Carseats)

library(ISLR)

names(Carseats)

?Carseats

plot=(medv~lstat, Carseats)

plot(medv~lstat,Carseats)

library(MASS)

names(Carseats)

fix(Carseats)

lm.fit=lm(Sales~lstat+Price+Urban+US ,data=Carseats)

lm.fit=lm(Sales~Price+Urban+US ,data=Carseats)

summary(lm.fit)

plot(lm.fit)

lm.fit=lm(Sales~Urban, Data=Carseats)

summary(Carseats)

pairs(Carseats)

lm.fit=lm(Sales~Urban+Advertising, Data=Carseats)

lm.fit=lm(Sales~Urban+Advertising ,data=Carseats)

summary(lm.fit)

lm.fit=lm(Sales~Urban+Advertising+Income+CompPrice+Population +Age+ShelveLoc+Education ,data=Carseats)

summary(lm.fit)

lm.fit=lm(Sales~Urban+Education+Population+CompPrice ,data=Carseats)

lm.fit=lm(Sales~Urban+Education+Population+CompPrice ,data=Carseats)

summary(lm.fit)

plot(lm.fit)

plot(lm.fit)

set.seed(1)

x <- 1:100

sum(x^2)

y <- 5 * x + rnorm(100, sd = 0.1)

sum(y^2)

fit.Y <- lm(y ~ x + 0)

fit.X <- lm(x ~ y + 0)

summary(fit.Y)

summary(fit.X)

y <- 100:1

sum(y^2)

summary(fit.X)

summary(fit.Y)

par(mfrow = c(2, 2))

plot(log(Auto\(displacement), Auto\)mpg)

plot(sqrt(Auto\(mpg), Auto\)weight)

plot((Auto\(acceleration)^2, Auto\)year)

fit2 <- lm(mpg ~ . - name, data = Auto)

summary(fit2)

plot(fit2)