Enter six data points - e.g car speed at one second intervals
from beginning of braking until car has stopped, or average
temperature at two week intervals from September to December.
Fit a linear model to your data.
CHALLENGE - Deviation is defined as the square root
of the sum of the squares of the vertical distances to
to linear model function.
Why not use some measure that depends on the
perpendicular distances to the linear model function?
CHALLENGE - If we can (almost) always fit a finite set of data with a
polynomial, why do we bother with statistical techniques like regression?
Why does it say almost?