Simple Linear Regression - Python Code

 import numpy as np

import matplotlib.pyplot as plt


x=np.array([1,2,3,4,5])

y=np.array([1.2,1.8,2.6,3.2,3.8])


xmean=np.mean(x)

ymean=np.mean(y)


nr=np.sum((x-xmean)*(y-ymean))

dr=np.sum((x-xmean) ** 2)


b1=nr/dr


b0=ymean-b1*xmean


print(f"Estimated coefficients : b0={b0},b1={b1}")


ypred_line=b0+b1*x


print(f"y_predicted_line : {ypred_line}")


print('Prediction for x=7')


x_new=7

ypred_new=b0+b1*x_new

print(f"Prediction for x :{x_new}, y:{ypred_new}")


plt.scatter(x,y,color='blue',label='Original Data')

plt.plot(x,ypred_line,color='red',label='Regression Line')

plt.xlabel('x')

plt.ylabel('y')

plt.title('Simple Linear Regression')

plt.legend()

plt.grid(True)

plt.show()

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