def total_sum_of_squares(y: Vector) -> float:
"""the total squared variation of y_i's from their mean"""
return sum(v ** 2 for v in de_mean(y))
def total_sum_of_squares(y: Vector) -> float:
"""the total squared variation of y_i's from their mean"""
return sum(v**2 for v in de_mean(y))
def total_sum_of_squares(y: Vector) -> float:
"""Suma odchyleń kwadratów wartości y_i od średniej."""
return sum(v**2 for v in de_mean(y))
from typing import Tuple
from scratch.linear_algebra import Vector
from scratch.statistics import correlation, standard_deviation, mean, de_mean
def least_squares_fit(x, y):
beta = correlation(x, y) * standard_deviation(y) / standard_deviation(x)
alpha = mean(y) - beta * mean(x)
return alpha, beta
x = [i for i in range(-100, 110, 10)]
y = [3 * i - 5 for i in x]
print(de_mean([1, 2, 3, 4, 5]))
print("x :", x)
print("y :", y)
print(least_squares_fit(x, y))
def total_sum_of_squares(y: Vector) -> float:
return sum(y_i**2 for y_i in de_mean(y))