Practical aspects — Linear Regression in layman terms
I won $100 on Monday, $200 on Tuesday, $300 on Wednesday, how much would I win on Thursday? If you answered $400 you just did linear regression!
The everyday predictions we make are mostly driven by linear regression. The number of miles you’ll run based on the time you run for and the energy level you have, the number of books you’ll read based on your new year resolution and last year’s number, the bonus you’ll get based on company performance and your own, house prices based on land size etc.
We constantly make predictions, e.g. how far we can throw the ball based on how forcefully we throw, time to travel given traffic conditions etc. Linear regression can be used as the simplest tool to make predictions on such relations. Not all of the above examples follow a linear trend though. Hence it is important to understand that even the linear regression can be the first attempt at understanding the data it may not always be ideal.
But look at the pattern above! One thing is common
‘Make a Prediction’ based on ‘some information’
Terminology-wise
‘prediction’ = dependent variable and
‘some information’ = independent variables.
