# Python Math: Describe linear regression

## Python Math: Exercise-61 with Solution

Write a Python program to 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).

**Sample Solution**:

**Python Code:**

```
#https://gist.github.com/cartr/6513044
# 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))
```

Sample 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

**Flowchart:**

**Python Code Editor:**

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