In the context of this exercise, what are some other examples of real data that linear regression can apply to?
In general, linear regression can apply to datasets for which there is a linear relationship between two variables.
One common example is housing price data vs a single parameter of the house, such as the number of rooms, square footage, and so on. Another example can be the household income vs the education level of the house owners. Linear regression can also apply to datasets that have the time, in hours, studied vs the grade received for an exam. Also, we can apply linear regression on data showing the number of transistors in a computer chip vs time in years, which is known as Moore’s law.
In addition to these, there are countless real-world datasets that linear regression can apply to, so feel free to find them and test out your linear regression models on!