https://www.codecademy.com/courses/learn-python-3/informationals/python3-reggies-linear-regression

that’s the link but it’s on jupyter notebook so you’d have to download the zip file.

I’ve just copied all previous code hopefully that helps.

def get_y(m, b, x):
y = m*x + b
return y
get_y(1, 0, 7) == 7
get_y(5, 10, 3) == 25
def calculate_error(m, b, point):
x_point, y_point = point
y = m*x_point + b
distance = abs(y - y_point)
return distance
#this is a line that looks like y = x, so (3, 3) should lie on it. thus, error should be 0:
print(calculate_error(1, 0, (3, 3)))
#the point (3, 4) should be 1 unit away from the line y = x:
print(calculate_error(1, 0, (3, 4)))
#the point (3, 3) should be 1 unit away from the line y = x - 1:
print(calculate_error(1, -1, (3, 3)))
#the point (3, 3) should be 5 units away from the line y = -x + 1:
print(calculate_error(-1, 1, (3, 3)))
datapoints = [(1, 2), (2, 0), (3, 4), (4, 4), (5, 3)]
def calculate_all_error(m, b, datapoints):
total_error = 0
for point in datapoints:
point_error = calculate_error(m, b, point)
total_error += point_error
return total_error