What is linear regression and how is it used in R?

What is linear regression and how is it used in R?

Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables. In R, you can use the lm() function to perform linear regression.

Can you show me a simple example of linear regression in R?

Sure! Here's a basic example:

# Sample data
x <- c(1, 2, 3, 4, 5)
y <- c(2, 3, 5, 7, 11)

# Fit linear model
model <- lm(y ~ x)

# Summary of the model
summary(model)

What does the summary of the model tell me?

The summary provides information about the coefficients, R-squared value, and p-values, which help you understand the strength and significance of the relationship between the variables.

How can I visualize the linear regression results?

You can use the ggplot2 package to visualize the results. Here's an example:

library(ggplot2)

# Create a scatter plot with the regression line
ggplot(data.frame(x, y), aes(x, y)) + 
  geom_point() + 
  geom_smooth(method='lm', col='blue')