R Markdown
head(data)
## ID city area rooms bathroom parking animal furniture floor rentAmount
## 1 0 1 240 3 3 4 acept furnished 6 8,000
## 2 1 0 64 2 1 1 acept not furnished 10 820
## 3 2 1 443 5 5 4 acept furnished 3 7,000
## 4 3 1 73 2 2 1 acept not furnished 12 1,250
## 5 4 1 19 1 1 0 not acept not furnished 6 1,200
## 6 5 1 13 1 1 0 acept not furnished 2 2,200
## fireInsurance hoa propertyTax
## 1 121 0 1,000
## 2 11 540 122
## 3 89 4,172 1,417
## 4 16 700 150
## 5 16 0 41
## 6 28 0 42
summary(data)
## ID city area rooms
## Min. : 0 Min. :0.0000 Min. : 10.0 Min. : 1.000
## 1st Qu.:1520 1st Qu.:1.0000 1st Qu.: 58.0 1st Qu.: 2.000
## Median :3040 Median :1.0000 Median : 100.0 Median : 3.000
## Mean :3040 Mean :0.8633 Mean : 151.1 Mean : 2.493
## 3rd Qu.:4559 3rd Qu.:1.0000 3rd Qu.: 200.0 3rd Qu.: 3.000
## Max. :6079 Max. :1.0000 Max. :24606.0 Max. :10.000
## bathroom parking animal furniture
## Min. : 1.000 Min. : 0.000 Length:6080 Length:6080
## 1st Qu.: 1.000 1st Qu.: 1.000 Class :character Class :character
## Median : 2.000 Median : 1.000 Mode :character Mode :character
## Mean : 2.342 Mean : 1.756
## 3rd Qu.: 3.000 3rd Qu.: 2.000
## Max. :10.000 Max. :12.000
## floor rentAmount fireInsurance hoa
## Min. : 1.000 Length:6080 Min. : 3.0 Length:6080
## 1st Qu.: 4.000 Class :character 1st Qu.: 23.0 Class :character
## Median : 6.000 Mode :character Median : 41.0 Mode :character
## Mean : 7.207 Mean : 58.2
## 3rd Qu.: 9.000 3rd Qu.: 77.0
## Max. :99.000 Max. :677.0
## propertyTax
## Length:6080
## Class :character
## Mode :character
##
##
##
Linear Regession
data$propertyTax <- as.numeric(gsub("\\.", "", data$propertyTax))
## Warning: NAs introduced by coercion
data$rentAmount <- as.numeric(gsub("\\.", "", data$rentAmount))
## Warning: NAs introduced by coercion
linear.model = lm(rentAmount~propertyTax, data = data) # build linear regression model on full data
summary(linear.model)
##
## Call:
## lm(formula = rentAmount ~ propertyTax, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -363.46 -82.75 25.21 117.27 216.51
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 7.825e+02 1.076e+01 72.721 <2e-16 ***
## propertyTax 3.723e-03 1.805e-01 0.021 0.984
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 140.8 on 299 degrees of freedom
## (5779 observations deleted due to missingness)
## Multiple R-squared: 1.423e-06, Adjusted R-squared: -0.003343
## F-statistic: 0.0004255 on 1 and 299 DF, p-value: 0.9836