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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.

Questo esercizio fa parte del corso

Introduction to Linear Modeling in Python

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Istruzioni dell'esercizio

  • Compute the deviations dx and dy.
  • Compute the normalized deviations zx and zy.
  • Call plot_cdfs() to see how both the raw and the normalized data compares.

Esercizio pratico interattivo

Prova a risolvere questo esercizio completando il codice di esempio.

# 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)
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