x <- c(5.6, 6.3, 7, 7.7, 8.4)
y <- c(8.8, 12.4, 14.8, 18.2, 20.8)
relation <- lm(y~x)
summary(relation)
## 
## Call:
## lm(formula = y ~ x)
## 
## Residuals:
##     1     2     3     4     5 
## -0.24  0.38 -0.20  0.22 -0.16 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept) -14.8000     1.0365  -14.28 0.000744 ***
## x             4.2571     0.1466   29.04 8.97e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.3246 on 3 degrees of freedom
## Multiple R-squared:  0.9965, Adjusted R-squared:  0.9953 
## F-statistic: 843.1 on 1 and 3 DF,  p-value: 8.971e-05
plot(y,x,col = "green",main = "Given points",
abline(lm(x~y)),cex = 1.3,pch = 16,xlab = "X axis",ylab = "Y axis")

equat = function(x,y){
  f = 24*x - 6*x*y^2 - 8*y^3
  return(c(x,y,f))
}
print(rbind(equat(-4,2),equat(4,-2)))
##      [,1] [,2] [,3]
## [1,]   -4    2  -64
## [2,]    4   -2   64