Univariate Linear Regression (relationship between the dependent variable y and the independent variable x is linear) using R programming Language for the blog post https://medium.com/@GalarnykMichael/univariate-linear-regression-using-r-programming-3db499bdd1e3#.kcm3t9rl3

LinearRegression.R

# Linear Regression predicts linear relationship between two variables

# Set path to Desktop
setwd("~/Desktop")

download.file(url = 'https://raw.githubusercontent.com/mGalarnyk/Python_Tutorials/master/Python_Basics/Linear_Regression/linear.csv'
              , destfile = 'linear.csv')
rawData=read.csv("linear.csv", header=T)

# Show first n entries of data.frame, notice NA values
head(rawData, 10)

linModel <- lm(y~x, data = rawData)

# Show attributes of linModel
attributes(linModel) 

# To show what happens with na.action, "omit" since data has NA
linModel$na.action

# Show coefficients of model
linModel$coefficients

# Predicting New Value based on our model
predict(linModel, data.frame(x = 3))

plot(y ~ x, data = rawData,
       xlab = "This labels the x axis",
       ylab = "This labels the y axis",
       main = "Scatter Plot"
)

abline(linModel, col = "red", lwd = 3)

So clear and concise!