Program to implement univariate Linear Regression to fit a straight line using least squares.
Developed by:LOGESHWARI.P
RegisterNumber:212221230055

import matplotlib.pyplot as plt
x=[5,6,3,2,6,7,1,2]
y=[2,3,6,5,8,3,5,8]
plt.scatter(x,y)
plt.show()

import numpy as np
import matplotlib.pyplot as plt

#assign input
x=np.array([0,1,2,3,4,5,6,7,8,9])
y=np.array([1,3,2,5,7,8,8,9,10,12])

#mean values of input
x_mean=np.mean(x)
print(x_mean)
y_mean=np.mean(y)
print(y_mean)

num=0
denum=0

for i in range(len(x)):
  num+=(x[i]-x_mean)*(y[i]-y_mean)
  denum+=(x[i]-x_mean)**2

#find m
m=num/denum

#find b
b=y_mean-m*x_mean
print("m",m)
print("b",b)

#find y_pred
y_pred=m*x+b
print(y_pred)

#plot graph
plt.scatter(x,y)
plt.plot(x,y_pred,color='green')
plt.show()