Untitled

library(datasets)
data("swiss")
View(swiss)
head(swiss)

##              Fertility Agriculture Examination Education Catholic
## Courtelary        80.2        17.0          15        12     9.96
## Delemont          83.1        45.1           6         9    84.84
## Franches-Mnt      92.5        39.7           5         5    93.40
## Moutier           85.8        36.5          12         7    33.77
## Neuveville        76.9        43.5          17        15     5.16
## Porrentruy        76.1        35.3           9         7    90.57
##              Infant.Mortality
## Courtelary               22.2
## Delemont                 22.2
## Franches-Mnt             20.2
## Moutier                  20.3
## Neuveville               20.6
## Porrentruy               26.6

summary(swiss)

##    Fertility      Agriculture     Examination      Education    
##  Min.   :35.00   Min.   : 1.20   Min.   : 3.00   Min.   : 1.00  
##  1st Qu.:64.70   1st Qu.:35.90   1st Qu.:12.00   1st Qu.: 6.00  
##  Median :70.40   Median :54.10   Median :16.00   Median : 8.00  
##  Mean   :70.14   Mean   :50.66   Mean   :16.49   Mean   :10.98  
##  3rd Qu.:78.45   3rd Qu.:67.65   3rd Qu.:22.00   3rd Qu.:12.00  
##  Max.   :92.50   Max.   :89.70   Max.   :37.00   Max.   :53.00  
##     Catholic       Infant.Mortality
##  Min.   :  2.150   Min.   :10.80   
##  1st Qu.:  5.195   1st Qu.:18.15   
##  Median : 15.140   Median :20.00   
##  Mean   : 41.144   Mean   :19.94   
##  3rd Qu.: 93.125   3rd Qu.:21.70   
##  Max.   :100.000   Max.   :26.60

plot(swiss$Fertility)

cor.test(swiss$Fertility,swiss$Infant.Mortality)

## 
##  Pearson's product-moment correlation
## 
## data:  swiss$Fertility and swiss$Infant.Mortality
## t = 3.0737, df = 45, p-value = 0.003585
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.1469699 0.6285366
## sample estimates:
##      cor 
## 0.416556

plot(swiss$Fertility,swiss$Infant.Mortality)

plot(swiss$Education,swiss$Infant.Mortality)

## R Markdown

summary(cars)

##      speed           dist       
##  Min.   : 4.0   Min.   :  2.00  
##  1st Qu.:12.0   1st Qu.: 26.00  
##  Median :15.0   Median : 36.00  
##  Mean   :15.4   Mean   : 42.98  
##  3rd Qu.:19.0   3rd Qu.: 56.00  
##  Max.   :25.0   Max.   :120.00

Including Plots

You can also embed plots, for example:

library(corrplot)

## corrplot 0.92 loaded

plot(swiss$Fertility)

cor.test(swiss$Fertility,swiss$Infant.Mortality)

## 
##  Pearson's product-moment correlation
## 
## data:  swiss$Fertility and swiss$Infant.Mortality
## t = 3.0737, df = 45, p-value = 0.003585
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
##  0.1469699 0.6285366
## sample estimates:
##      cor 
## 0.416556

plot(swiss$Fertility,swiss$Infant.Mortality)

plot(swiss$Education,swiss$Infant.Mortality)