1. 皮尔逊相关系数 (Pearson Correlation Coefficient):
1.1 衡量两个值线性相关强度的量
1.2 取值范围 [-1, 1]:
正向相关: >0, 负向相关：<0, 无相关性：=0
2. R平方值:
2.1定义：决定系数，反应因变量的全部变异能通过回归关系被自变量解释的比例。
2.2 描述：如R平方为0.8，则表示回归关系可以解释因变量80%的变异。换句话说，如果我们能控制自变量不变，则因变量的变异程度会减少80%
2.3： 简单线性回归：R^2 = r * r
多元线性回归：
Python实现;
import numpy as npfrom astropy.units import Ybarnimport mathdef computeCorrelation(X, Y): xBar = np.mean(X) yBar = np.mean(Y) SSR = 0 varX = 0 varY = 0 for i in range(0 , len(X)): diffXXBar = X[i] - xBar diffYYBar = Y[i] - yBar SSR += (diffXXBar * diffYYBar) varX += diffXXBar**2 varY += diffYYBar**2 SST = math.sqrt(varX * varY) return SSR / SSTtestX = [1, 3, 8, 7, 9]testY = [10, 12, 24, 21, 34]print (computeCorrelation(testX, testY))