JuniorTheoryCommon

What does this program print?

Python

import numpy as np

x = np.array([1, 2, 3, 4])
y = np.array([3, 5, 7, 9])
w = ((x - x.mean()) * (y - y.mean())).sum() / ((x - x.mean()) ** 2).sum()
b = y.mean() - w * x.mean()
print(w, b)

2.0 1.0

Expecting 2.0 6.0: the intercept is y.mean() - w * x.mean(), so the slope times the mean of x is subtracted: 6.0 - 2.0 * 2.5 = 1.0.
Expecting 2 1 because x and y hold integers: .mean() always returns a float, so w and b are floats and print as 2.0 and 1.0.

What would w and b become if every value of y were shifted up by 10?
Why does this slope formula break when every value of x is the same?

Back to questions Open topic in roadmap →Answer it yourself — Quiz

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JuniorTheoryCommon

What does this program print?

Python

import numpy as np

x = np.array([1, 2, 3, 4])
y = np.array([3, 5, 7, 9])
w = ((x - x.mean()) * (y - y.mean())).sum() / ((x - x.mean()) ** 2).sum()
b = y.mean() - w * x.mean()
print(w, b)

2.0 1.0

Expecting 2.0 6.0: the intercept is y.mean() - w * x.mean(), so the slope times the mean of x is subtracted: 6.0 - 2.0 * 2.5 = 1.0.
Expecting 2 1 because x and y hold integers: .mean() always returns a float, so w and b are floats and print as 2.0 and 1.0.

What would w and b become if every value of y were shifted up by 10?
Why does this slope formula break when every value of x is the same?

Back to questions Open topic in roadmap →Answer it yourself — Quiz