As such, linear regression is often called the ‘ line of best fit’. It determines the linear function or the straight line that best represents your data’s distribution. This is when linear regression comes in handy. When you plot your data observations on the x- and y- axis of a chart, you might observe that though the points don’t exactly follow a straight line, they do have a somewhat linear pattern to them. Linear regression is the simplest of regression analysis methods. What regression then does is model the relationship between these two variables by fitting an equation to the data distribution. If X is one of these independent variables and Y, the dependent variable, then it would be possible to plot observed data of age and productivity into a scatter chart. It may be dependent on factors such as age, work-life balance, hours worked, etc. So productivity is the dependent variable. We know that productivity of an employee is dependent on other factors. Let’s take our productivity problem as an example. When performing regression analysis, you are essentially trying to determine the impact of an independent variable on a dependent variable. This can help you focus on factors that matter the most so that you can optimize them and bring about an increase in the overall productivity of employees. So you can use it to determine the factors that influence, say productivity of employees and then use this as a template to predict how changes in these factors are going to bring changes in productivity. When it comes to business, regression can be used for both forecasting and optimization. In medical sciences, it can be used to determine how cognitive functions change with aging.
Regression can be applied in agriculture to find out how rainfall affects crop yields. In today’s world, Regression can be applied to a number of areas, such as business, agriculture, medical sciences, and many others.
In this article, we are going to discuss what Linear Regression in Python is and how to perform it using the Statsmodels python library. It is a statistical technique which is now widely being used in various areas of machine learning. In the simplest terms, regression is the method of finding relationships between different phenomena.