Last Update: February 21, 2022
Simple linear regression in R can be fitted using
lm function. Main parameters within
lm function are
y ~ x model description and
data.frame object including model variables. Therefore,
lm(y ~ x, data = model.data) code line fits model using variables included within
As example, we can fit simple linear regression of house price explained by its lot size using data included within
HousePrices object .
First, we load packages
AER for data and
ggplot2 for charting .
In : library(AER) library(ggplot2)
Second, we create
HousePrices data object from
AER package using
data function and print first six rows and two columns of data using
head function to view
In : data(HousePrices) head(HousePrices[,1:2])
Out : price lotsize 1 42000 5850 2 38500 4000 3 49500 3060 4 60500 6650 5 61000 6360 6 66000 4160
Third, we draw scatter chart with regression line which doesn’t display its confidence interval.
In : ggplot(data = HousePrices, aes(x = lotsize, y = price)) + geom_point() + geom_smooth(method = "lm", se = FALSE)
Fourth, we fit model with
lm function using variables within
HousePrices data object, store outcome within
slr object and print its coefficients estimates. Within
lm function, parameter
formula = price ~ lotsize fits model where house price is explained by its lot size.
In : slr <- lm(formula = price ~ lotsize, data = HousePrices) slr
Out : Call: lm(formula = price ~ lotsize, data = HousePrices) Coefficients: (Intercept) lotsize 34136.192 6.599
My online courses are hosted at Teachable website.
For more details on this concept, you can view my Linear Regression in R Course.
 Data Description: Sales prices of houses sold in the city of Windsor, Canada, during July, August and September, 1987.
Original Source: Anglin, P., and Gencay, R. (1996). Semiparametric Estimation of a Hedonic Price Function. Journal of Applied Econometrics, 11, 633–648.
 AER R Package. Christian Kleiber and Achim Zeileis. (2008). Applied Econometrics with R. Springer-Verlag, New York.
ggplot2 R Package. Hadley Wickham (2016). ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag, New York.