What is the statistics.linear_regression() method in Python?
Overview
In a linear function, simple linear regression defines the connection between an independent variable x and a dependent variable y.
y = slope * x + intercept
Note: Refer to A deep dive into linear regression to learn more about linear regression.
The linear_regression() method is used to get the slope and intercept of a simple linear regression given the values x and y using the ordinary least squares estimation method. This method was introduced in Python version 3.10.
The inputs x and y should be the same length and should at least have two data points.
Syntax
linear_regression(x, y)
Parameters
x: This is the independent variable.y: This is the dependent variable.
Return value
The method returns the slope and intercept.
Code
Let’s look at the code below:
import statisticsx = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]y = [11 ,13, 12, 15, 17, 18, 18, 19, 20, 22]slope, intercept = statistics.linear_regression(x, y)print("Slope - ", slope)print("Intercept - ", intercept)
Explanation
- Line 1: We import the
statisticsmodule. - Line 3: We define the independent variable
x. - Line 4: We define the dependent variable
y. - Line 5: We obtain the
slopeandinterceptofxandyusing thelinear_regression()method. - Lines 8 and 9: We print the
slopeandinterceptvalue.
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