python-scipyHow do I use Python and SciPy to perform linear regression?

Linear regression is a statistical method used to find the relationship between two variables. With Python and SciPy, you can use the least-squares method to fit a linear regression model.

Example code

import scipy.stats as st

x = [1, 2, 3, 4, 5]
y = [1, 4, 9, 16, 25]

slope, intercept, r_value, p_value, std_err = st.linregress(x,y)

print("slope: %f    intercept: %f" % (slope, intercept))

Output example

slope: 4.000000    intercept: 0.000000

Code explanation

• import scipy.stats as st imports the SciPy library.
• x = [1, 2, 3, 4, 5] and y = [1, 4, 9, 16, 25] creates two lists of data points.
• slope, intercept, r_value, p_value, std_err = st.linregress(x,y) uses the SciPy linregress function to fit a linear regression model to the data.
• print("slope: %f intercept: %f" % (slope, intercept)) prints the slope and intercept of the linear regression model.

Helpful links

• SciPy Documentation: https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.linregress.html
• Python Tutorial: https://docs.python.org/3/tutorial/index.html

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