Linear Regression with statsmodels in Python Template
The following Linear Regression with Statsmodels in Python free .ipynb template shows how to solve a simple linear regression problem using the Ordinary Least Squares statsmodels library. We are going to examine the causal relationship between the independent variable in the dataset - SAT score of a student, and the dependent variable -the GPA score. This database is read with the help of the pandas library. Download and unzip the .zip file in a new folder. Inside the folder you will find a .csv and a .ipynb file. The first one contains the database and the second one contains the Python code. Open the .ipynb file using Jupyter notebook.
Who is it for
Everybody who has ever dealt with machine learning and statistics has inevitably solved linear regression problems. This template is for any Data Analyst, Data Scientist, or Machine Learning Engineer who is interested in learning how to explain the causal relationship between two variables and provide insightful information which can later be used for making informed business decisions.
How it can help you
Regression analysis is used when we need to quantify the relationship between dependent and independent variables. This analytical skill is in high demand in the fields of medicine, agriculture, professional sports and especially in the corporate world where it is used to predict people's behaviors on the market.