SLR works on datasets that have one independent and one dependent variable. It plots both in XY dimensional space, draws trend lines based on the dataset, and finally makes a prediction by choosing the best fitting line. However, we now need to think about what would happen if the number of dependent variables is more than one. This is where multiple linear regression comes into the picture. Multiple linear regression (MLR) takes multiple independent variables and plots them over n-dimensions in order to make a prediction.
We will now be working on a different dataset that contains information relating to 50 startup companies. The data essentially consists of expenditure made on various verticals of the company ...
