# R : Add Linear Regression Equation and RSquare to Graph

In this article, we would see how to add linear regression equation and r-squared to a graph in R. It is very useful when we need to document or present our statistical results. Many people are familiar with R-square as a performance metrics for linear regression. If you are novice in linear regression technique, you can read this article - Linear Regression with R

Create Sample Data

The following program prepares data that is used to demonstrate the method of adding regression equation and rsquare to graph.
x = c(1:250)
mydata= data.frame(x, y= 30 + 2.5 * x + rnorm(250,sd = 25))
library(ggplot2)
R Function
linear = function(k) {
z <- list(xx = format(coef(k)[1], digits = 2),
yy = format(abs(coef(k)[2]), digits = 2),
r2 = format(summary(k)\$r.squared, digits = 3));
if (coef(k)[2] >= 0)  {
eq <- substitute(italic(hat(y)) == xx + yy %.% italic(x)*","~~italic(r)^2~"="~r2,z)
} else {
eq <- substitute(italic(hat(y)) == xx - yy %.% italic(x)*","~~italic(r)^2~"="~r2,z)
}
as.character(as.expression(eq));
}
fo = y ~ x
linplot <- ggplot(data = mydata, aes(x = x, y = y)) + geom_smooth(method = "lm", se=FALSE, color="black", formula = fo) +  geom_point()
linplot1 = linplot + annotate("text", x = 100, y = 500, label = linear(lm(fo, mydata)), colour="black", size = 5, parse=TRUE)
linplot1
 Regression Line
Share
Related Posts

Deepanshu founded ListenData with a simple objective - Make analytics easy to understand and follow. He has over 10 years of experience in data science. During his tenure, he has worked with global clients in various domains like Banking, Insurance, Private Equity, Telecom and Human Resource.

0 Response to "R : Add Linear Regression Equation and RSquare to Graph"

Next → ← Prev
Looks like you are using an ad blocker!

To continue reading you need to turnoff adblocker and refresh the page. We rely on advertising to help fund our site. Please whitelist us if you enjoy our content.