Well done! You’ve calculated the variance of a data set. The full equation for the variance is as follows:
Let’s dissect this equation a bit.
- Variance is usually represented by the symbol sigma squared.
- We start by taking every point in the dataset — from point number
1to point number
N— and finding the difference between that point and the mean.
- Next, we square each difference to make all differences positive.
- Finally, we average those squared differences by adding them together and dividing by
N, the total number of points in the dataset.
All of this work can be done quickly using a function we provided. The
variance() function takes a list of numbers as a parameter and returns the variance of that dataset.
dataset <- c(3, 5, -2, 49, 10) var <- variance(dataset)
We’ve imported the same two datasets from the beginning of the lesson. Run the code to see a histogram of the two datasets. This time, the histograms are plotted on the same graph to help visualize the difference in spread.
Which dataset do you expect to have a larger variance?
Scroll down in the code to find where we’ve definied
teacher_two_variance. Set those variables equal to the variance of each dataset using the