Reggies Linear Reggresion - datapoints are missing?

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1

Where does the datapoints in part 2 come from? First I used the points from part 1 but they are wrong. In the solution they used the following list:
datapoints = [(1, 2), (2, 0), (3, 4), (4, 4), (5, 3)]
In the tasks file they aren’t mentioned so I have no clue where they come from?
As far as I understand this data has to be given or can should I calculate it somehow?

Reggies Linear Regression link

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2

You are right, points are needed for the second part, the exercise says to use the same but the slope and the intercept do not give what the exercise says.

3

it might be these:

first set:

datapoints = [(1, 2), (2, 0), (3, 4), (4, 4), (5, 3)]

second set:

datapoints = [(1, 1), (3, 3), (5, 5), (-1, -1)]

… although I’m not sure about those.

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4

It’s true, but the slope and intercept are only correct if we declare the first datapoints again.
I did this in my code from part two:

possible_ms = [x * 0.1 for x in range(-100, 101)]
possible_bs = [x * 0.1 for x in range(-200, 201)]

datapoints = [(1, 2), (2, 0), (3, 4), (4, 4), (5, 3)]
smallest_error = float("inf")
best_m = 0
best_b = 0

for m in possible_ms:
    for b in possible_bs:
        error = calculate_all_error(m, b, datapoints)
        if error < smallest_error:
            smallest_error = error
            best_m = m
            best_b = b

print(best_m, best_b, smallest_error)

Output: 0.30000000000000004 1.7000000000000002 4.999999999999999