salary hike

empdata<-read.csv("E:\\Data science\\emp_data.csv")
View(empdata)
summary(empdata)

##        sh            cor       
##  Min.   :1580   Min.   :60.00  
##  1st Qu.:1618   1st Qu.:65.75  
##  Median :1675   Median :71.00  
##  Mean   :1689   Mean   :72.90  
##  3rd Qu.:1724   3rd Qu.:78.75  
##  Max.   :1870   Max.   :92.00

attach(empdata)
cor(sh,cor)

## [1] -0.9117216

plot(sh,cor)

windows()
qqnorm(sh)

windows()
m1<-lm("sh~cor",data=empdata)
m1

## 
## Call:
## lm(formula = "sh~cor", data = empdata)
## 
## Coefficients:
## (Intercept)          cor  
##    2285.365       -8.186

pv<-predict(m1,empdata)
pv

##        1        2        3        4        5        6        7        8 
## 1532.246 1589.548 1630.479 1671.409 1695.967 1712.340 1728.712 1753.270 
##        9       10 
## 1777.828 1794.200

pv1<-as.data.frame(pv)
pv1

##          pv
## 1  1532.246
## 2  1589.548
## 3  1630.479
## 4  1671.409
## 5  1695.967
## 6  1712.340
## 7  1728.712
## 8  1753.270
## 9  1777.828
## 10 1794.200

final<-cbind(empdata,pv1)
final

##      sh cor       pv
## 1  1580  92 1532.246
## 2  1600  85 1589.548
## 3  1610  80 1630.479
## 4  1640  75 1671.409
## 5  1660  72 1695.967
## 6  1690  70 1712.340
## 7  1706  68 1728.712
## 8  1730  65 1753.270
## 9  1800  62 1777.828
## 10 1870  60 1794.200