Mean, Deviation, & Standard Deviation
The mean describes the center of the data. The standard deviation describes the spread of the data. But to compare two variables, it is convenient to normalize both. In this exercise, you are provided with two arrays of data, which are highly correlated, and you will compute and visualize the normalized deviations of each array.
Diese Übung ist Teil des Kurses
Introduction to Linear Modeling in Python
Anleitung zur Übung
- Compute the deviations
dxanddy. - Compute the normalized deviations
zxandzy. - Call
plot_cdfs()to see how both the raw and the normalized data compares.
Interaktive Übung
Versuche dich an dieser Übung, indem du diesen Beispielcode vervollständigst.
# Compute the deviations by subtracting the mean offset
dx = x - np.____(x)
dy = y - np.____(y)
# Normalize the data by dividing the deviations by the standard deviation
zx = dx / np.____(x)
zy = dy / np.____(y)
# Plot comparisons of the raw data and the normalized data
fig = plot_cdfs(dx, dy, zx, zy)