Multiple R squared I
The R squared represents the proportion of improvement in the model from using the regression line over using the mean. In our case, it looks at how we can predict how much someone will like us based on how much money we give them, and how much we smile at them, compared to just using the average amount that someone likes us.
R gives us this automatically when we use summary() on the model we found using lm(). summary() tells us a lot about the model. To extract the R squared in particular, we can use the $. For example, summary(*regression model*)$r.squared would return the R squared value. Let's try this!
This exercise is part of the course
Inferential Statistics
Exercise instructions
- In your console, use the
summary()function on ourlm()model, and assign the resulting object to variablemod1. - In your console, use the
$to print the value of the R-squared frommod1.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Vector containing the amount of money you gave participants (predictor)
money <- c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)
# Vector containing how much you smiled (predictor)
smile <- c(0.6, 0.7, 1.0, 0.1, 0.3, 0.1, 0.4, 0.8, 0.9, 0.2)
# Vector containing the amount the participants liked you (response)
liking <- c(2.2, 2.8, 4.5, 3.1, 8.7, 5.0, 4.5, 8.8, 9.0, 9.2)
# Assign the summary of lm(liking ~ smile + money) to 'mod1'
mod1 <- summary(lm(liking ~ smile + money))
# Print the R-squared of 'mod1'