【原创】r语言房价回归分析代码

data=read.table("data.txt",header=T)

head(data)

## case Taxes Beds Baths New Price Size

## 1 1 3104 4 2 0 279900 2048

## 2 2 1173 2 1 0 146500 912

## 3 3 3076 4 2 0 237700 1654

## 4 4 1608 3 2 0 200000 2068

## 5 5 1454 3 3 0 159900 1477

## 6 6 2997 3 2 1 499900 3153

# A. Please open the dataset, omit any missing values, and name it myda ta.

mydata=na.omit(data)

# B

plot(mydata[,-1])

# C. Using -ggplot- suite

colnames(mydata)

## [1] "case""Taxes""Beds""Baths""New""Price""Size"

library(ggplot2)

ggplot(mydata, aes(x = Size, y = Price)) + geom_point(aes( )) +

geom_smooth()

ggplot(mydata, aes(x = Taxes, y = Price)) +

geom_point(aes( )) +

geom_smooth()

# D. Do your visualizations show a positive, negative,

# or no relationship?

# E. Is there evidence that you may need to transform any of your varia bles? Why? Motivate

# your answer by showing any relevant statistics or graphs

ggplot(mydata, aes(x =(Size) , y =log(Price))) +

geom_point(aes( )) +

geom_smooth()

ggplot(mydata, aes(x = (Taxes), y =log(Price))) + geom_point(aes( )) +

geom_smooth()