Describe linear regressionΒΆ
Describe linear regression.
Note :
A linear regression line has an equation of the form
Y = a + bX,
where X is the explanatory variable
and Y is the dependent variable.
The slope of the line is b,
and a is the intercept (the value of y when x = 0).
Expected output:
Enter the number of data points: 2
X1: 1
Y1: 2
X2: 3
Y2: 4
Best fit line:
y = 1.0x + 1.0
Enter a value to calculate: 12
y = 13.0
# Define the data
data = set()
count = int(input("Enter the number of data points: "))
for i in range(count):
x = float(input("X" + str(i + 1) + ": "))
y = float(input("Y" + str(i + 1) + ": "))
data.add((x,y))
# Find the average x and y
avgx = 0.0
avgy = 0.0
for i in data:
avgx += i[0]/len(data)
avgy += i[1]/len(data)
# Find the sums
totalxx = 0
totalxy = 0
for i in data:
totalxx += (i[0]-avgx)**2
totalxy += (i[0]-avgx)*(i[1]-avgy)
# Slope/intercept form
m = totalxy/totalxx
b = avgy - m*avgx
print("Best fit line:")
print("y = "+str(m) + "x + " + str(b))
x = float(input("Enter a value to calculate: "))
print("y = " + str(m*x + b))
Output:
Enter the number of data points: 2
X1: 1
Y1: 2
X2: 3
Y2: 4
Best fit line:
y = 1.0x + 1.0
Enter a value to calculate: 10
y = 11.0