python 求线性回归_stats.linregress(x, y)

线性回归

python 求线性回归的函数是 linregress(x,y) 函数；
slope是斜率，
intercept是截距，
r_value 是相关系数

from scipy import stats
import numpy as np
import pylab

x = np.array([1, 2, 5, 7, 10, 15])
y = np.array([2, 6, 7, 9, 14, 19])

slope, intercept, r_value, p_value, slope_std_error = stats.linregress(x, y)

predict_y = intercept + slope * x
pred_error = y - predict_y
degrees_of_freedom = len(x) - 2
residual_std_error = np.sqrt(np.sum(pred_error**2) / degrees_of_freedom)

# Plotting
pylab.plot(x, y, 'o')
pylab.plot(x, predict_y, 'k-')
pylab.show()
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